DataStage Version 8 on Information Server

Enterprise PACKs

SAP BW Pack o BAPI: (Staging Business API) loads from any source to BW. o OpenHub: extract data from BW.

SAP R/3 Pack o ABAP: (Advanced Business Application Processing) auto generate ABAP, Extraction Object Builder, SQL Builder, Load and execute ABAP from DataStage, CPI-C Data Transfer, FTP Data Transfer, ABAP syntax check, background execution of ABAP. o IDoc: create source system, IDoc listener for extract, receive IDocs, send IDocs. o BAPI: BAPI explorer, import export Tables Parameters Activation, call and commit BAPI.

Siebel Pack o EIM: (data integration manager) interface tables o Business Component: access business views via Siebel Java Data Bean o Direct Access: use a metadata browser to select data to extract o Hierarchy: for extracts from Siebel to SAP BW.

Oracle Applications Pack o Oracle flex fields: extract using enhanced processing techniques. o Oracle reference data structures: simplified access using the Hierarchy Access component. o Metadata browser and importer

DataStage Pack for PeopleSoft Enterprise o Import business metadata via a metadata browser. o Extract data from PeopleSoft tables and trees.

JD Edwards Pack o Standard ODBC calls o Pre-joined database tables via business views Database Connectivity The common connection objects functionality means the very wide range of DataStage database connections are now available across Information Server products. Latest supported databases for version 8:

DB2 8.1, 8.2 and 9.1

Oracle 9i, 10i, 10gR2 not Oracle 8

SQL Server 2005 plus stored procedures.

Teradata v2r5.1, v2r6.0, v2r6.1 (DB server) / 8.1 (TTU) plus Teradata Parallel Transport (TPT) and stored procedures and macro support, reject links for bulk loads, restart capability for parallel bulk loads.

Sybase ASE 15, Sybase IQ 11.5, 12.5, 12.7

Informix 10 (IDS)

SAS 612, 8.1, 9.1 and 9.1.3

IBM WS MQ 6.1, WS MB 5.1

Netezza v3.1

ODBC 3.5 standard and level 3 compliant

UniData 6 and UniVerse ?

Red Brick Source

New Stages in DataStage Version 8

New Stages in Datastage Version 8 A new stage from the IBM software family, new stages from new partners and the convergence of QualityStage functions into Datastage. Apart from the SCD stage these all come at an additional cost.

WebSphere Federation and Classic Federation

Netezza Enterprise Stage

SFTP Enterprise Stage

iWay Enterprise Stage

Slowly Changing Dimension: for type 1 and type 2 SCDs.

Six QualityStage stages New Functions in Existing Stages

Complex Flat File Stage: Multi Format File (MFF) in addition to existing cobol file support.

Surrogate Key Generator: now maintains the key source via integrated state file or DBMS sequence.

Lookup Stage: range lookups by defining checking high and low range fields on the input or reference data table. Updatable in memory lookups.

Transformer Stage: new surrogate key functions Initialize() and GetNextKey().

Enterprise FTP Stage: now choose between ftp and sftp transfer. Source :

When to choose Server or Parallel Data stage job

1. The choice of server or parallel depends upon time to implement, functionality and cost.
2. When we have lots of functionality to implement for lower volume and hardware is less and ease of implementation we can go for Server jobs.
3. Parallel jobs are costly due to high scale of hardware , difficult to implement, extreme processing capabilities for absurd volumes with vast array of operators for high-performance manipulation.
4. When the data volume is less it is better to go for Server job as parallel jobs can have a longer start up time.
5. When data volume is high, it is better to choose parallel job than server job. Parallel job will be a lot faster than server job even if it runs on single node. The obvious incentive for going parallel is data volume. Parallel jobs can remove bottlenecks and run across multiple nodes in a cluster for almost unlimited scalability. At this point parallel jobs become the faster and easier option. A parallel sort stage is lot faster than server stage. A Transformer stage in parallel job with the same transformations in server job is faster. Even on one node with a compiled transformer stage, the parallel version was three times faster. On 1 node configuration that does not have a lot of parallel processing also we can still get big performance improvements from an Enterprise Edition job. The improvements will be multiplied 10 or more than that if we work on 2CPU machines and two nodes in most stages.
6. Parallel jobs take advantage of both pipeline parallelism and partitioning parallelism.
7. We can improve the performance of server job by enabling inter process row buffering. This helps stages to exchange data as soon as it is available in the link. IPC stage also helps passive stage to read data from another as soon as data is available. In other words, stages do not have to wait for the entire set of records to be read first and then transferred to the next stage. Link partitioner and link collector stages can be used to achieve a certain degree of partitioning parallelism.
8. Look up with sequential file is possible in parallel jobs and not possible in server jobs.

Data Mart

A data mart is a subset of an organizational data store, usually oriented to a specific purpose or major data subject, that may be distributed to support business needs.[1] Data marts are analytical data stores designed to focus on specific business functions for a specific community within an organization. Data marts are often derived from subsets of data in a data warehouse, though in the bottom-up data warehouse design methodology the data warehouse is created from the union of organizational data marts.

In practice, the terms data mart and data warehouse each tend to imply the presence of the other in some form. However, most writers using the term seem to agree that the design of a data mart tends to start from an analysis of user needs and that a data warehouse tends to start from an analysis of what data already exists and how it can be collected in such a way that the data can later be used. A data warehouse is a central aggregation of data (which can be distributed physically); a data mart is a data repository that may or may not derive from a data warehouse and that emphasizes ease of access and usability for a particular designed purpose. In general, a data warehouse tends to be a strategic but somewhat unfinished concept; a data mart tends to be tactical and aimed at meeting an immediate need.

One writer, Marc Demerest, suggests combining the ideas into a Universal Data Architecture (UDA). In practice, many products and companies offering data warehouse services also tend to offer data mart capabilities or services.

There can be multiple data marts inside a single corporation; each one relevant to one or more business units for which it was designed. DMs may or may not be dependent or related to other data marts in a single corporation. If the data marts are designed using conformed facts and dimensions, then they will be related. In some deployments, each department or business unit is considered the owner of its data mart including all the hardware, software and data.[2] This enables each department to use, manipulate and develop their data any way they see fit; without altering information inside other data marts or the data warehouse. In other deployments where conformed dimensions are used, this business unit ownership will not hold true for shared dimensions like customer, product, etc.

Design schemas:

Star Schema or dimensional model is a fairly popular design choice, as it enables a relational database to emulate the analytical functionality of a multidimensional database.

Snowflake Schema Advantages of creating a data mart

Easy access to frequently needed data

Creates collective view by a group of users

Improves end-user response time

Ease of creation

Lower cost than implementing a full Data warehouse

Potential users are more clearly defined than in a full Data warehouse

Dependent data mart

According to the Inmon school of data warehousing, a dependent data mart is a logical subset (view) or a physical subset (extract) of a larger data warehouse, isolated for one of the following reasons:

A need for a special data model or schema: e.g., to restructure for OLAP

Performance: to offload the data mart to a separate computer for greater efficiency or to obviate the need to manage that workload on the centralized data warehouse.

Security: to separate an authorized data subset selectively

Expediency: to bypass the data governance and authorizations required to incorporate a new application on the Enterprise Data Warehouse

Proving Ground: to demonstrate the viability and ROI (return on investment) potential of an application prior to migrating it to the Enterprise Data Warehouse

Politics: a coping strategy for IT (Information Technology) in situations where a user group has more influence than funding or is not a good citizen on the centralized data warehouse.

Politics: a coping strategy for consumers of data in situations where a data warehouse team is unable to create a usable data warehouse.

According to the Inmon school of data warehousing, tradeoffs inherent with data marts include limited scalability, duplication of data, data inconsistency with other silos of information, and inability to leverage enterprise sources of data.

OLTP Online transaction processing

OLTP stands for Online transaction processing Online transaction processing, or OLTP, refers to a class of systems that facilitate and manage transaction-oriented applications, typically for data entry and retrieval transaction processing. The term is somewhat ambiguous; some understand a "transaction" in the context of computer or database transactions, while others (such as the Transaction Processing Performance Council) define it in terms of business or commercial transactions.OLTP has also been used to refer to processing in which the system responds immediately to user requests. An automatic teller machine (ATM) for a bank is an example of a commercial transaction processing application.
The technology is used in a number of industries, including banking, airlines, mailorder, supermarkets, and manufacturing. Applications include electronic banking, order processing, employee time clock systems, e-commerce, and eTrading. The most widely used OLTP system is probably IBM's CICS.

Requirements: Online transaction processing increasingly requires support for transactions that span a network and may include more than one company. For this reason, new OLTP software uses client/server processing and brokering software that allows transactions to run on different computer platforms in a network.
In large applications, efficient OLTP may depend on sophisticated transaction management software (such as CICS) and/or database optimization tactics to facilitate the processing of large numbers of concurrent updates to an OLTP-oriented database.
For even more demanding decentralized database systems, OLTP brokering programs can distribute transaction processing among multiple computers on a network. OLTP is often integrated into SOA service-oriented architecture and Web services.

Advantages: Online Transaction Processing has two key benefits: simplicity and efficiency.
Reduced paper trails and the faster, more accurate forecasts for revenues and expenses are both examples of how OLTP makes things simpler for businesses. It also provides a concrete foundation for a stable organization because of the timely updating. Another simplicity factor is that of allowing consumers the choice of how they want to pay, making it that much more enticing to make transactions.
OLTP is proven efficient because it vastly broadens the consumer base for an organization, the individual processes are faster, and it’s available 24/7.
Disadvantages:
It is a great tool for any organization, but in using OLTP, there are a few things to be wary of: the security issues and economic costs.
One of the benefits of OLTP is also an attribute to a potential problem. The worldwide availability that this system provides to companies makes their databases that much more susceptible to intruders and hackers.
For B2B transactions, businesses must go offline to complete certain steps of an individual process, causing buyers and suppliers to miss out on some of the efficiency benefits that the system provides. As simple as OLTP is, the simplest disruption in the system has the potential to cause a great deal of problems, causing a waste of both time and money. Another economic cost is the potential for server failures. This can cause delays or even wipe out an immeasurable amount of data.

OLAP On Line Analytical Processing,MOLAP,ROLAP,HOLAP

OLAP is an acronym for On Line Analytical Processing. OLAP performs multidimensional analysis of business data and provides the capability for complex calculations, trend analysis, and sophisticated data modeling. It is quickly becoming the fundamental foundation for Intelligent Solutions including Business Performance Management, Planning, Budgeting, Forecasting, Financial Reporting, Analysis, Simulation Models, Knowledge Discovery, and Data Warehouse Reporting. OLAP enables end-users to perform ad hoc analysis of data in multiple dimensions, thereby providing the insight and understanding they need for better decision making. Databases configured for OLAP employ a multidimensional data model, allowing for complex analytical and ad-hoc queries with a rapid execution time. They borrow aspects of navigational databases and hierarchical databases that are speedier. Nigel Pendse has suggested that an alternative and perhaps more descriptive term to describe the concept of OLAP is Fast Analysis of Shared Multidimensional Information (FASMI). The output of an OLAP query is typically displayed in a matrix (or pivot) format. The dimensions form the row and column of the matrix; the measures, the values. Functionality: In the core of any OLAP system is a concept of an OLAP cube (also called a multidimensional cube or a hypercube). It consists of numeric facts called measures which are categorized by dimensions. The cube metadata is typically created from a star schema or snowflake schema of tables in a relational database. Measures are derived from the records in the fact table and dimensions are derived from the dimension tables.

Aggregations: It has been claimed that for complex queries OLAP cubes can produce an answer in around 0.1% of the time for the same query on OLTP relational data. The single most important mechanism in OLAP which allows it to achieve such performance is the use of aggregations. Aggregations are built from the fact table by changing the granularity on specific dimensions and aggregating up data along these dimensions. The number of possible aggregations is determined by every possible combination of dimension granularities.
The combination of all possible aggregations and the base data contains the answers to every query which can be answered from the data [8]. Due to the potentially large number of aggregations to be calculated, often only a predetermined number are fully calculated while the remainder are solved on demand. The problem of deciding which aggregations (a.k.a. views) to calculate is known as the view selection problem. View selection can be constrained by the total size of the selected set of aggregations, the time to update them from changes in the base data, or both. The objective of view selection is typically to minimize the average time to answer OLAP queries, although some studies also minimize the update time as well. Many different approaches have been taken to view selection (which is NP-Complete), including greedy algorithms, randomized search, genetic algorithms and A* search algorithm
A very effective way to support aggregation and other common OLAP operations is the use of bitmap indexes.

Types: OLAP systems have been traditionally categorized using the following taxonomy.[9] Multidimensional
MOLAP:
MOLAP is the 'classic' form of OLAP and is sometimes referred to as just OLAP. MOLAP uses database structures that are generally optimal for attributes such as time period, location, product or account code. The way that each dimension will be aggregated is defined in advance by one or more hierarchies.
Relational:
ROLAP: ROLAP works directly with relational databases. The base data and the dimension tables are stored as relational tables and new tables are created to hold the aggregated information. Depends on a specialized schema design.

Hybrid: HOLAP
There is no clear agreement across the industry as to what constitutes "Hybrid OLAP", except that a database will divide data between relational and specialized storage. For example, for some vendors, a HOLAP database will use relational tables to hold the larger quantities of detailed data, and use specialized storage for at least some aspects of the smaller quantities of more-aggregate or less-detailed data. Comparison among these three OLAP's:
Each type has certain benefits, although there is disagreement about the specifics of the benefits between providers.
Some MOLAP implementations are prone to database explosion. Database explosion is a phenomenon causing vast amounts of storage space to be used by MOLAP databases when certain common conditions are met: high number of dimensions, pre-calculated results and sparse multidimensional data. The typical mitigation technique for database explosion is not to materialize all the possible aggregation, but only the optimal subset of aggregations based on the desired performance vs. storage trade off.
MOLAP generally delivers better performance due to specialized indexing and storage optimizations. MOLAP also needs less storage space compared to ROLAP because the specialized storage typically includes compression techniques.
ROLAP is generally more scalable. However, large volume pre-processing is difficult to implement efficiently so it is frequently skipped. ROLAP query performance can therefore suffer.
Since ROLAP relies more on the database to perform calculations, it has more limitations in the specialized functions it can use.
HOLAP encompasses a range of solutions that attempt to mix the best of ROLAP and MOLAP. It can generally pre-process quickly, scale well, and offer good function support.
Courtesy:Wikipedia

Unix Commands Quick Reference

cat filename1 > filename2 :
This overwrite contents of filename2 with filename1

cat filename1 » filename2 :
This appends contents of filename1 to filename2.

cd /usr:
Changes current directory to /usr directory

cd .. :
Change current directory to previous higher directory.

cd :
Change to home of current userid.

chgrp group1 filename1 :
Change group id to group 1 for filename1.

chgrp -R group1 * :
Changes group id of all files in current and subdirectories to group 1.

chmod ugo+rwx filename1:
Add read/write/execute permission to filename1 for user/owner, group and others (world).

chmod o x filename1 :
Remove execute from others (world)

chmod 751 filename1 :
Set rwx for user/owner, group and others; r=4, w=2, x=1, rwx=7 rx=5, rw=6, wx=3, none=0.

chown sam filename1 :
Change owner of file filename1 to sam.

chown -R sam * :
Change owner to sam for all files in current and subdirectories.

clear :
Clear the terminal screen.

compress filename1 :
Compress file filename1 and replace it with filename1.Z

cp filename1 filename2 :
Copy file filename1 to filename2 destroying the contents of filename2.

cp -i * /usr/local/bin :
Copy all files in current directory to /usr/local/bin directory; Prompt before overwriting files (i)

cpio :
Copy file archives to disk/tape

crontab -e :
Edit crontab file for current user

crontab -e bill :
Edit crontab file for user bill

crontab -l :
List crontab entries for current userid

csh :
Start the c shell process

cut -d:
-f1,5 /etc/passwd :
Extract the 1st and 5th fields (username & real name) from file /etc/passwd where delimiter is colon

who | cut -d" " -f1:
List login names from who command

date :
Display current date string

date +%D :
Display current date, MM/DD/YY format

dd :
Copy file(s) to/from raw devices

df :
Displays free disk blocks and modes on file systems.

df -k :
Displays free space in kilobytes for mounted file systems

echo name :
Displays literal "name" on screen

echo $PATH :
Displays PATH environment variable

ed/edit/ex :
Alternative line editors, see vi

env Displays current environment variables or allows setting

file filename1 :
Determines and displays type of file for filename1 (text, data, executable, directory, symbolic link...etc...)

find /usr/opt/bin -name "filename1*" -print :
Starts searching in /usr/opt/bin for files starting with

filename1, If found prints the full file names and continues searching subdirectories

find . -type f -print | xargs grep -i [PATTERN] :
Recursive grep for a pattern in a file (searches through files in subdirectories)

find . ! -mtime - | /usr/bin/xargs rm -rf :
Finds and removes files older than specified

finger sam :
Displays data about user session for sam

ftp solar :
Establishes a File Transfer Protocol session over the network between current host and a host named solar; See man pages for additional ftp commands

grep jdoe /etc/passwd :
Searches the file /etc/passwd searching for string "jdoe"; If found, displays

grep -i Sam filename1:
Search filename1 for upper or lower case string of Sam and display lines found

groups sam :
List groups that sam is a member of

head filename1 :
Display first few lines of filename1

head -50 filename1:
Display first fifty lines of filename1

id :
List current user id and any group ids

kill -9 1351 :
Terminate process number 1351

ksh:
Start Korn Shell command interpreter; See man pages; Preferred shell for most users

ln -s filename1 /usr/opt/filename2 :
Create a symbolic link named /usr/opt/filename2 that points to filename1; See man pages

lp -d lp1 filename1 :
Print filename1 on destination printer lp1

lpstat -d :
Displays name of default printer, if any

lpstat -a :
Lists printers accepting print requests

lpstat -s :
Displays most everything regarding printing

lpstat -u sam :
Displays status of sam's print jobs

ls -al :
Displays all files in wide listing

ls -al *.doc :
Displays files ending with .doc

ls -al /bin/k*:
Displays files starting with k in /bin directory

man --is Online UNIX manual:

man-pages:
It gives detailed instructions on all of the commands listed here and a lot more.See man man for more...

mail sam :
Starts mail message to sam

mailx sam :
Nicer looking mail utility

mkdir -p /usr/opt/dirx:
Creates dirx below /usr/opt

make:
Code compilation utility

mkdir dirx:
Creates directory dirx

more filename1 :
Displays single pages from filename1 pausing after each page.for many options see man pages

mv filename1 /usr/opt/ :
Moves filename1 to directory /usr/opt; Unlike the cp (copy) command, mv removes file from origin

netstat -i:
Show the TCP/IP network interfaces

netstat -r:
Show network route table

netstat -rn:
Displays routing information but bypasses hostname lookup

netstat -a | more :
Show the state of all sockets

newgrp group1 :
Changes current group to group 1

news :
Displays unread files from /usr/news or /var/news

nice/renice :
Adjusts process’ execution priority

Unix Commands from p to z:

passwd:
Allows changing your login password

ps :
Lists all of current user's live processes

ps -ef :
List all users processes that are executing

pwd:
Displays current working directory you are in

rcp filename1 hostb:
/usr/local/bin :
Copies filename1 from current host system to hostb, and places it in the /usr/local/bin directory; The .rhosts or hosts.equiv files must be setup to allow action

rksh:
Starts restricted Korn Shell session

rlogin hostb :
Logs into remote host name hostb

rm filename1 :
Deletes filename1 from the disk without recourse

rm -i filename1 :
Deletes filename1 after prompting for verification

rmdir dirx :
Deletes directory dirx

rmdir -r dirx:
Deletes directory and all contents

rsh:
Restricted version of Bourne Shell for security

sar :
System Activity Reporter

sh :
Bourne Shell command interpreter; Alternative to Korn Shell and C shell but is the default on most systems; Older version that is losing popularity

sleep 3 :
Pauses for 3 seconds and continues

stty sane:
Attempts to restore terminal settings after they are hosed; Use CTRL-J with this command

stty erase ^H :
Use to reset backspace/delete; ^H is the key you may want to use for backspace/delete;

su sam:
Log on as user sam

su - sam:
Log on as sam, and execute his profile too

tail filename1 :
Display last few lines of filename1

tail -50 filename1 :
Display last fifty lines of filename1

tail -f :
Continually reads updating file; Great for monitoring a log file while being written

tar -cvf /dev/rmt/0c /usr/bin/* :
Tape archive utility; Copies all files in /usr/bin directory to tape device /dev/rmt/

tar -xvf /dev/rmt/0 /usr/bin/ :
Extracts all files from tape device /dev/rmt/0 and writes them to /usr/bin/

tar -tvf /dev/rmt/0c :
Read tape on device /dev/rmt/0c and lists contents in verbose mode

tee:
Used in scripts to split output to two outputs. Usually used with a pipe command (|)

tee -a /tmp/filename1:
Append the output to filename1 without overwriting its original content

telnet hostb:
Create a remote terminal on hostb

touch filename1 :
Creates an empty file named filename1; Changes modification time to current time if the file already exists

uname -a:
Lists 0/S revision, host name, hardware

uncompress filename1 :
Uncompresses file with .Zsuffix, created by compress command previously

uptime :
Displays current time, time logged-in,number of users etc

users:
Displays current logged-in users in a listing

uucp :
UNIX-to-UNIX copy utility; See man pages

view filename1:
A read only version of vi editor

w :
Combination of uptime, who and ps -a commands

wall :
Write to all; Allows entry of message to be sent to line 25 of all terminals; End message with a CTRLD command

wc -l filename1:
Utility that counts the number of lines in filename1

wc -c filename1 :
Utility that counts the number of bytes in filename1; -m provides number of characters

wc -w filename1 :
Utility that counts the number of the words in filename1

whence filename2:
Prints path name location of executable filename2

which filename2 :
Similar to whence command

who Displays login name, terminal name, date, and time of login, of users currently logged in

who am i :
Displays effective user id of user

who -b :
Displays date/time of last reboot

who -r :
Displays current system run level

Informatica Certification FAQ's

General

What do I need to bring with me to my public class? It is being held at an Informatica facility. Nothing. All required learning materials are provided in the classroom.

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I found the Informatica course I would like to take, but there is not a location close to me on the schedule. For additional information, call Global Education Services at 1-866-311-5338, or you can e-mail us at training_registrar@informatica.com.

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What is On-site Training? In addition to our publicly-scheduled classes, most of our instructor-led courses can be delivered as an on-site class at your location. On-site training events are designed to meet your needs, while reducing the impact on your business and training budget. To request on-site training call Global Education Services at 1-866-311-5338, or you can e-mail us at training_registrar@informatica.com. What is included in a standard on-site event? Typically pricing for an on-site event will include an Informatica instructor, travel and expenses (within the US) all courseware and set up documentation. Payments

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What are pre-paid training credits? Training credits may be purchased and applied towards any Informatica Global Education Services' offering, including: Public training courses, on-site training courses, Informatica Virtual Academy, eLearning, and Informatica Professional Certification exams. The cost of training credits depends on the quantity purchased. Training credits are valid for use for one year from the date of purchase. Public Course and IVA Pricing: public courses require 10 training credits per one 8-hour day of instruction. For courses with durations less than one day, the credits are prorated.On-site (Customer Site) Course Pricing: On-site courses require 64 training credits per one 8-hour day of instruction for up to 8 students. Additional students (up to 15 students) are 8 credits per student per day of instruction. The training credit fees cover all course fees and materials, and instructor travel expenses, within the United States. The Customer is responsible for any facility rental charges if class is not held at the Customer's facility. Discount Schedule: Training Credits - Tier 1 (0-99 credits), Price per credit $80 USD (representing a 0% discount) Training Credits - Tier 2 (100-199 credits), Price per credit $76 USD (representing a 5% discount) Training Credits - Tier 3 (200+ credits), Price per credit $72 USD (representing a 10% discount) Bulk Purchases Corporate Pass (384 credits) $26,000 USD (representing a 15% discount) Corporate Pass Plus (768 credits) $48,000 USD (representing a 21%discount)

My company has purchased Informatica Pre-paid Training Credits, how do I use them? When registering online the attendee should obtain the purchase credit access key from the designated Credit Administrator. During the on-line registration processes the attendee will be prompted to choose a payment method. Choose "Purchase Credits" and enter the access key in the field provided.

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What is the cancellation policy for Informatica Global Education? Requests for cancellations or date transfers need to be received by Informatica Global Education Services at least ten (10) business days prior to the event start date in order to receive a full refund. If a cancellation or reschedule request is received less than ten (10) business days before the start date, the penalty of 100% of the cost of the course will be applied so none of the fee will be refunded. Refunds will not be allowed for "no-shows". This cancellation policy is strictly enforced.

What happens if Informatica needs to cancel or reschedule a course? Informatica reserves the right to cancel events for any reason at anytime. Cancellation liability for Informatica if Informatica cancels the course is limited to the return of course payment ONLY. Informatica will not reimburse registrants for any other costs including but not limited to any travel cancellation fees or penalties, including airfare and hotel costs. PLEASE NOTE: If your registration status is either "New", or "In Progress" you have not been confirmed for the class and it is recommended that you do not make any travel arrangements until you have received a confirmation e-mail letting you know the class and registration is confirmed.

How will I know if my course has been rescheduled? Informatica Global Education Services reserves the right to reschedule or cancel a course due to low enrollment or if necessitated by other circumstances. Informatica Global Education Services will contact you via e-mail or phone to inform you of the change of schedule. Once you have been notified you may reschedule or receive a full credit. Informatica Global Education Services shall not be liable for any other costs including but not limited to any non-refundable travel arrangements if a course is rescheduled or canceled. Informatica Virtual Academy (IVA)

What does IVA stand for? Informatica's Virtual Academy combines the interactivity of instructor-led classroom learning with the comfort and convenience of learning in your customary work environment. The virtual Academy uses Microsoft's "Live Meeting" tool to deliver our expert-led workshops using audio and video right at your desk. With this technology, you can interact with the instructor and other students and ask questions using either audio or text messaging. Labs are supported through Informatica's and Hatsize virtual lab environment, so you don't have to tie up your licenses to complete the hands on experience. Each class is broken into individual modules, each lasting about half a day. Sessions are scheduled frequently and at different times of the day, allowing you to pick the times that are most convenient to you. After you register for a class and your payment is processed, you will receive detailed information about how to access your Virtual Classes, download the materials and connect to the session.

Is an IVA class the same format as an E-learning class? No, IVA training is in a Live Meeting format with the instructor on line with you during the entire class, whereas E-learning is a pre-recorded session that can be accessed at any time. E-learning is a self-pace format that must be completed in one year's time.

Where can I attend IVA training? You may attend IVA training at a location of your choice; home, office or conference room, as long as you have access to high-speed internet with no firewall, no proxy server and no VPN; and an pen phone line.You will also need internet Explorer 6 or higher, monitor resolution set to 1024 x 768, and a telephone connection with a speaker phone or headset for hands free communication.

Will I get courseware with my IVA class? Yes, your courseware will be sent to you either via e-mail in PDF format or via Federal Express depending on the size of the manual.

When can I expect the IVA courseware to be shipped / sent? As soon as your registration has been completed all data, paperwork and payments have been processed, and the class has been confirmed. Courseware will be either e-mailed in PDF format or will be sent to the address you provided in your Informatica Global Education on-line profile.

Will I need to download or install Informatica software to attend an IVA class? You will need to verify the latest version of JavaScript and possibly download the latest version of software for Microsoft Live Meeting Manager; you will not need to install Informatica software. After registration, an e-mail acknowledgement will be sent to you with test links for these downloads. Courtesy:informatica.com

Informatica Professional Certification Program

In this competitive IT market place, you need to differentiate yourself. Demonstrate your technical ability by becoming an Informatica Certified Professional.

Informatica Professional Certification proves you have the knowledge and skills needed to meet today’s complex data integration challenges. You will be recognized among the elite Informatica users who possess the technical know-how and ability to design, implement, use, and support the Informatica solution. In addition, the Informatica Certification Program provides an objective measurement for benchmarking and validating technical Informatica product expertise.

By being Informatica certified, you established your professional credibility with your employer and within the competitive IT industry. These tangible, industry-recognized credentials can help you succeed in your career, improve your productivity, and increase your marketability.
Take your expertise to the next level with the Informatica Professional Certification.

There are three levels of certifications available:

1. Administrator;
2. Developer; and
3. Consultant

Certification Level	Number of Exams Required	Description
	For PowerCenter administrators, testers, and project managers you need to attain a passing score (70 percent or higher) on two exams: Architecture and Administration Advanced Administration	Administrator. Become an specialist in managing and maintaining the infrastructure of platform integration projects
	For PowerCenter transformation, mapping, and mapplet developers, you need to attain a passing score on three exams: Architecture and Administration Mapping Design Advanced Mapping Design	Developer. Become an specialist in developing, troubleshooting and maintaining transformations, mappings, and mapplets
	For PowerCenter experts you need to attain a passing score on five exams: Architecture and Administration Mapping Design Advanced Administration Advanced Mapping Design Enablement Technologies.	Consultant. Become a true data integration expert by meeting the criteria of both an Informatica Certified Administrator and Designer

An Informatica Professional Certification is based strictly on knowledge level you can attain through a combination of hands-on project work and Informatica training. Before taking an exam, Informatica provides you with a Skill Set Inventory to ensure that you have a detailed understanding of every topic that will be covered in a particular exam. All exams are multiple choice and administered over the Web.
Learn more about the Informatica Professional Certification exams by reading the FAQ here

Datastage DsAdmin Questions related to Unix

1. List the files in current directory sorted by size ? - ls -l | grep ^- | sort -nr
2. List the hidden files in current directory ? - ls -a1 | grep "^\."
3. Delete blank lines in a file ? - cat sample.txt | grep -v ‘^$’ > new_sample.txt
4. Search for a sample string in particular files ? - grep .Debug. *.confHere grep uses the string .Debug. to search in all files with extension..conf. under current directory.
5. Display the last newly appending lines of a file during appendingdata to the same file by some processes ? - tail .f Debug.logHere tail shows the newly appended data into Debug.log by some processes/user.
6. Display the Disk Usage of file sizes under each directory in currentDirectory ? - du -k * | sort .nr (or) du .k . | sort -nr
7. Change to a directory, which is having very long name ? - cd CDMA_3X_GEN*Here original directory name is . .CDMA_3X_GENERATION_DATA..
8. Display the all files recursively with path under current directory ? - find . -depth -print
9. Set the Display automatically for the current new user ? - export DISPLAY=`eval ‘who am i | cut -d"(" -f2 | cut -d")" -f1′`Here in above command, see single quote, double quote, grave ascent is used. Observe carefully.
10. Display the processes, which are running under yourusername ? - ps .aef | grep MaheshvjHere, Maheshvj is the username.
11. List some Hot Keys for bash shell ? - Ctrl+l . Clears the Screen. Ctrl+r . Does a search in previously given commands in shell. Ctrl+u - Clears the typing before the hotkey. Ctrl+a . Places cursor at the beginning of the command at shell. Ctrl+e . Places cursor at the end of the command at shell. Ctrl+d . Kills the shell. Ctrl+z . Places the currently running process into background.
12. Display the files in the directory by file size ? - ls .ltr | sort .nr .k 5
13. How to save man pages to a file ? - man | col .b > Example : man top | col .b > top_help.txt
14. How to know the date & time for . when script is executed ? - Add the following script line in shell script.eval echo "Script is executed at `date`" >> timeinfo.infHere, .timeinfo.inf. contains date & time details ie., when script is executed and history related to execution.
15. How do you find out drive statistics ? - iostat -E
16. Display disk usage in Kilobytes ? - du -k
17. Display top ten largest files/directories ? - du -sk * | sort -nr | head
18. How much space is used for users in kilobytes ? - quot -af
19. How to create null file ? - cat /dev/null > filename1
20. Access common commands quicker ? - ps -ef | grep -i $@
21. Display the page size of memory ? - pagesize -a
22. Display Ethernet Address arp table ? - arp -a
23. Display the no.of active established connections to localhost ? - netstat -a | grep EST
24. Display the state of interfaces used for TCP/IP traffice ? - netstat -i
25. Display the parent/child tree of a process ? - ptree Example: ptree 1267
26. Show the working directory of a process ? - pwdx Example: pwdx 1267
27. Display the processes current open files ? - pfiles Example: pfiles 1267
28. Display the inter-process communication facility status ? - ipcs
29. Display the top most process utilizing most CPU ? - top .b 1
30. Alternative for top command ? - prstat -a

Datastage DsAdmin Questions

1. Have you created User groups and Users? $ group -c ourgroup $ group -m groupname userid $ group -o groupname userid $ group -O groupname userid # adduser --ingroup grname userid
2. How to kill the process? $ ps $kill -9/-1 PID
3. How to Unlock DataStage Jobs if the job is used by the another user or Hanged out?

   su - dsadm {enter your password for dsadm, else you can use root} cd `cat /.dshome` . ./dsenv bin/uvsh list.readu {find the row that shows your lock, look over to the USERNO column and get that number} UNLOCK USER nnnnn ALL QUIT

   • CD To $DSHOME/../Projects/ProjectName
   • Type the Following and press Enger. INSERT INTO VOC (F0, F1, F2, F3, F4, F5) VALUES ('UNLOCK','V', 'list_readu','E','BV','unlock')
     1. cd ${INSTALLATION_PATH}/DSEngine/bin
     2. ./dsenv
     3. ./uv -admin -stop
4. How to Add Unlock command to Vocabulary file(VOC)? CD To $DSHOME/../Projects/ProjectName INSERT INTO VOC (F0, F1, F2, F3, F4, F5) VALUES ('UNLOCK','V', 'list_readu','E','BV','unlock')
5. What is the command to Restart the DataStage Server? What is UV over there
6. Tell me some problems you may encounter when the DataStage running on UNIX platforms? 1. Running out of file units, 2. Running out of memory(Heap error), 3. open connection, 4. ODBC connection problems.
7. What is Heap Error? Anything to do with "heap" is about allocation of memory resources. Either install more memory in your server(s), or reduce overall demand for memory, perhaps by running less no. of jobs simultaneously, or by running on a configuration with less no. of processing nodes.
8. What happens when you shut down the Datastage server without closing all client connections? There may be an open connection from a Datastage client, Without shutting down the client processes, sockets are released on most platforms after the timeout period of about 6 - 10 minutes, depending on system tuning.
9. Which command is used to know whether the datastage server is running or not? ps -ef | grep dsrpc (this process should not be running when DataStage has stopped successfully) OR #netstat | grep dsrpcd
10. How do you restart the failure job in sequencer using Administrator or Director? Sequence(Add check points on failure)

About Informatica Sessions

SESSION LOGS:

Information that reside in a session log:

- Allocation of system shared memory
- Execution of Pre-session commands/ Post-session commands
- Session Initialization
- Creation of SQL commands for reader/writer threads
- Start/End timings for target loading
- Error encountered during session
- Load summary of Reader/Writer/ DTM statistics

Other Information

- By default, the server generates log files based on the server code page.

Thread Identifier

Ex: CMN_1039

Reader and Writer thread codes have 3 digit and Transformation codes have 4 digits.

The number following a thread name indicate the following:
(a) Target load order group number
(b) Source pipeline number
(c) Partition number
(d) Aggregate/ Rank boundary number


Log File Codes:

Error Codes Description

BR -   Related to reader process, including ERP, relational and flat file.
CMN -  Related to database, memory allocation
DBGR -  Related to debugger
EP-  External Procedure
LM -  Load Manager
TM -  DTM
REP -  Repository
WRT -  Writer

 
Load Summary

(a) Inserted
(b) Updated
(c) Deleted
(d) Rejected

Statistics details

(a) Requested rows shows the no of rows the writer actually received for the specified operation
(b) Applied rows shows the number of rows the writer successfully applied to the target (Without Error)
(c) Rejected rows show the no of rows the writer could not apply to the target
(d) Affected rows shows the no of rows affected by the specified operation

Detailed transformation statistics

The server reports the following details for each transformation in the mapping

(a) Name of Transformation
(b) No of I/P rows and name of the Input source
(c) No of O/P rows and name of the output target
(d) No of rows dropped

Tracing Levels

Normal - Initialization and status information, Errors encountered, Transformation errors, rows skipped, summarize session details (Not at the level of individual rows)

Terse - Initialization information as well as error messages, and notification of rejected data

Verbose Init - Addition to normal tracing, Names of Index, Data files used and detailed transformation statistics.
Verbose Data - Addition to Verbose Init, Each row that passes in to mapping detailed transformation statistics.


NOTE

When you enter tracing level in the session property sheet, you override tracing levels configured for transformations in the mapping.
 
MULTIPLE SERVERS

With Power Center, we can register and run multiple servers against a local or global repository. Hence you can distribute the repository session load across available servers to improve overall performance. (You can use only one Power Mart server in a local repository)

Issues in Server Organization

- Moving target database into the appropriate server machine may improve efficiency
- All Sessions/Batches using data from other sessions/batches need to use the same server and be incorporated into the same batch.
- Server with different speed/sizes can be used for handling most complicated sessions.

Session/Batch Behavior

- By default, every session/batch run on its associated Informatica server. That is selected in property sheet.
- In batches, that contain sessions with various servers, the property goes to the servers, that’s of outer most batch.
 

Session Failures and Recovering Sessions

Two types of errors occurs in the server
- Non-Fatal
- Fatal

(a) Non-Fatal Errors

It is  an error that does not force the session to stop on its first occurrence. Establish the error threshold in the session property sheet with the stop on option. When you enable this option, the server counts Non-Fatal errors that occur in the reader, writer and transformations.

Reader errors can include alignment errors while running a session in Unicode mode.

Writer errors can include key constraint violations, loading NULL into the NOT-NULL field and database errors.

Transformation errors can include conversion errors and any condition set up as an ERROR,. Such as NULL Input.

(b) Fatal Errors

This occurs when the server can not access the source, target or repository. This can include loss of connection or target database errors, such as lack of database space to load data.

If the session uses normalizer (or) sequence generator transformations, the server can not update the sequence values in the repository, and a fatal error occurs.

(c) Others
Usages of ABORT function in mapping logic, to abort a session when the server encounters a transformation error.

Stopping the server using pmcmd (or) Server Manager


Performing Recovery

- When the server starts a recovery session, it reads the OPB_SRVR_RECOVERY table and notes the rowid of the last row commited to the target database. The server then reads all sources again and starts processing from the next rowid.
- By default, perform recovery is disabled in setup. Hence it won’t make entries in OPB_SRVR_RECOVERY table.
- The recovery session moves through the states of normal session schedule, waiting to run, Initializing, running, completed and failed. If the initial recovery fails, you can run recovery as many times.
- The normal reject loading process can also be done in session recovery process.
- The performance of recovery might be low, if 
o Mapping contain mapping variables
o Commit interval is high


Un recoverable Sessions

Under certain circumstances, when a session does not complete, you need to truncate the target and run the session from the beginning.

USER_TAB_COMMENTS Stores comment information on tables.

USER_COL_COMMENTS Stores comment information for columns.

USER_CONSTRAINTS CONTRAINT_TYPE column will list the first character of the first word that best describes each type of constraint.

ALL_CONSTRAINTS CONTRAINT_TYPE column will list the first character of the first word that best describes each type of constraint.

USER_OBJECTS Can be used to verify the validity status of all user database objects.

ALL_OBJECTS Can be used to verify the validity status of all database objects.

USER_UPDATABLE_COLUMNS COLUMN_NAME and UPDATABLE will tell you whether the columns in a complex view can be modified.

USER_INDEXES Contains the name of the index and it uniqueness.

USER_IND_COLUMNS Contains the index name, the table name, and the column name.

USER_SYS_PRIVS Shows all privileges associated with this user.

SESSION_PRIVS Shows all privileges available in this session.

USER_ROLE_PRIVS Identifies the roles granted to you.

ROLE_ROLE_PRIVS Identifies the roles granted to other roles in the database.

ROLE_TAB_PRIVS Identifies object privileges granted to roles.

ROLE_SYS_PRIVS Identifies system privileges granted to roles.

SESSION_ROLES Identifies roles available to the current session.

Grant Privileges..System Privileges and Object Privileges

Granting system and object privileges is accomplished with the grant command. Example: GRANT create session TO turner or GRANT select, update, insert ON emp TO turner (NOTE, this object privilege syntax does not work when granting privileges to a single column - correct syntax is GRANT privilege (column_name) ON table TO user;).

System Privileges:

1. Database Access These privileges control who accesses the database, when he or she can access it, and what he or she can do regarding management of his or her restricted session. Privileges include create session, alter session, and restricted session.
2. Users These privileges are used to manage users in the Oracle database. Typically, these privileges are reserved for DBAs or security administrators. Privileges include create user, become user, alter user, and drop user.
3. Tables These privileges govern which users can create and maintain tables. The privileges include create table, create any table, alter any table, backup any table, drop any table, lock any table, comment any table, select any table, insert any table, update any table, and delete any table. The create table or create any table privilege also enables you to drop the table. The create table privileges also bestows the ability to create indexes on the table and to run the analyze command on the table. To be able to truncate a table, you must have the drop any table privilege granted to you.
4. Indexes The privileges include create any index, alter any index, and drop any index. You should note that no create index system privilege exists. the create table privilege also enables you to alter and drop indexes that you won and that are associated with the table.
5. Synonyms These privileges include create synonym, create any synonym, drop any synonym, create public synonym, and drop public synonym. The create synonym privilege also enables you to alter and drop synonyms that you own.
6. Views Privileges include create view, create any view, and drop any view. The create view privilege also enables you to alter and drop views that you own.
7. Sequences Privileges include create sequence, create any sequence, alter any sequence, drop any sequence, and select any sequence. The create sequence privilege also enables you to drop sequences that you own.
8. Roles Roles are objects that can be used for simplified privilege management. You create a role, grant privileges to it, and then grant the role to users. Privileges include create role, drop any role, grant any role, and alter any role.
9. Transactions These privileges are for resolving in-doubt distributed transactions being processed on the Oracle database. Privileges include force transaction and force any transaction.
10. PL/SQL These privileges enable you to create, run, and manage those different types of blocks. Privileges include create procedure, create any procedure, alter any procedure, drop any procedure, and execute any procedure. The create procedure privilege also enables you to alter and drop PL/SQL blocks that you own.
11. Triggers A trigger is a PL/SQL block in Oracle that executes when a specified DML activity occurs on the table to which the trigger is associated. Privileges include create trigger, create any trigger, alter any trigger, and drop any trigger. The create trigger privilege also enables you to alter and drop triggers that you own.

Object Privileges:

1. select Permits the grantee of this object privilege to access the date in a table, sequence, view, or snapshot.
2. insert Permits the grantee of this object privilege to insert data into a table or, in some cases, a view. You can also restrict this privilege to specified columns of a table.
3. update Permits the granted to update data in a table or view. You can also restrict this privilege to specified columns of a table.
4. delete Permits the granted to delete data in a table or view. You can also restrict this privilege to specified columns of a table.
5. alter Permits the grantee of this object privilege to alter the definition of a table or sequence only; the alter privileges on all other database objects are considered system privileges.
6. index Permits the grantee of this object privilege to create an index on a table already defined.
7. references Permits the grantee of this object privilege to create or alter a table in order to crate a foreign key constraint against data in the reference table.
8. execute Permits the grantee of this object privilege to run a stored procedure or function.

Cognos Questions,Cognos FAQ's -II

1)how to create catalog?
2)If i want to include views in my catalog is it possible?.
3)tell me abt Styles?.have you created any styles?.
4)what is the difference between Snapshot and Hotfile?.
5)tell me cube creation steps?.
6)If you are developing model..how many windows are appear on the screen?.
7)what is dimension line?.
8)If you create cube how many dimensions are allowd into your dimension line?any restrictions?.
9)what is the extension of snapshot?.
10)extension of hotfile?.
11)your catalog size?.
12)how many cubes you developed?.
13)tell me the dimensions?
14)what is cube group?.
15)what is the relationship between dimension and facts?.
16)how to protect the cube data?.
17)If i don’t want to show the particular dimension in my cube is it posible?.
18)tell me the views in transformer?.
19)what is user classes?.
20)what reports you developed in powerplay?(dont say predefined reports like single line,multiline etc).
21)cube sources?it allowd relational databases?.
22)how can you extract the different databases intothe catalog?.
23)How to see erros in impromptu?.
24)loops in cognos?have you across his type of loops in cognos?.
25)how to create hotfile?.what is extension?.
26)what is UPFRONT?
27)what is webreports?
28)what is ticketing?.
29)what is macro have you developed any macros?.
30)cube size?
31)how many types of dimensions?.
32)what is semiadditive facts,additive facts?
33)how many types of facts?.
34)have you used cognos7?
35)what is incemental aggregation and incemental update?.
36)If model changes any changes in cube?

Cognos Questions,FAQ's

1. What is the difference between Cognos,BO?.
2. The loops in BO,
3. Which version u used cognos and BO?.
4. The reports developed in Cognos?.
5. The reports developed in BO?
6. What is dimension
7. )What are the types of dimension
8. )The tools u used in cognos?.
9. )Cognos supports drilldown,drillacross,drillthru?.
10. What are the steps to create cube?.
11. how much size your cube?.
12. Your cube source?.
13. What are the sources allowed into the Cube?.
14. How to select views at the catalolg creation?.
15. What is cascading promt?.
16. What is the difference between catalogpick list,report picklist,file picklist?.
17. how to secure your catalog?.
18. How to secure your cube?.
19. How to improve your cube performance?.
20. Waht is cube groups and uses of that ?.
21. what is upfront in cognos?.
22. What is MAcro?.Have u developed any macros in cognos?.
23. What type od catalog u created in Cognos?.
24. after creating the cube it will be saved in what extension?.
25. After creating the model it will be saved in what extension?.
26. The impromptu report will be saved default extension?.
27. types of reports in Impropmtu?.
28. Types of reports in powerplay?.
29. The modes in powerplay?.What is the default mode?.
30. Views in transformer?.
31. How can you hide the dimensions in cube?.
32. What is the difference between reporter and explorer?.
33. how to extract the two databes into the one catalog?.
34. what is catalog?.What it contains?.
35. The difference between catalog and Datamart?.
36. what is snapshot?.what is hotfile?.
37. how many cubes u created in transformer?.
38. Scheduling in cognos?.
39. What is OLAP?Is cognos OLAP?.
40. Webreports in Cognos?.
41. Linking of reports in cognos?.
42. what problems u faced at the catalog creation?.
43. what problems u faced at the cube creation.?
44. how many windows are come at the creation of model?.
45. how to send the cube to others?.Is there any option?.
46. what is the difference between .MDL and .MDC?.
47. If i want to change database is there any changes in your catalog?.
48. If I want to change the database is there any changes in your hotfile?.
49. Is there any changes in your cube if the database Changes?.
50. what is incremental aggregation in cube?.

Bitmap Index,c,Bitmap Join Indexes

Bitmap indexes are widely used in data warehousing environments. The environments typically have large amounts of data and ad hoc queries, but a low level of concurrent DML transactions. For such applications, bitmap indexing provides:

Reduced response time for large classes of ad hoc queries

Reduced storage requirements compared to other indexing techniques

Dramatic performance gains even on hardware with a relatively small number of CPUs or a small amount of memory

Efficient maintenance during parallel DML and loads

Fully indexing a large table with a traditional B-tree index can be prohibitively expensive in terms of space because the indexes can be several times larger than the data in the table. Bitmap indexes are typically only a fraction of the size of the indexed data in the table.

An index provides pointers to the rows in a table that contain a given key value. A regular index stores a list of rowids for each key corresponding to the rows with that key value. In a bitmap index, a bitmap for each key value replaces a list of rowids.

Each bit in the bitmap corresponds to a possible rowid, and if the bit is set, it means that the row with the corresponding rowid contains the key value. A mapping function converts the bit position to an actual rowid, so that the bitmap index provides the same functionality as a regular index. If the number of different key values is small, bitmap indexes save space.

Bitmap indexes are most effective for queries that contain multiple conditions in the WHERE clause. Rows that satisfy some, but not all, conditions are filtered out before the table itself is accessed. This improves response time, often dramatically. Benefits for Data Warehousing Applications:

Bitmap indexes are primarily intended for data warehousing applications where users query the data rather than update it. They are not suitable for OLTP applications with large numbers of concurrent transactions modifying the data.

Parallel query and parallel DML work with bitmap indexes as they do with traditional indexes. Bitmap indexing also supports parallel create indexes and concatenated indexes.

Cardinality

The advantages of using bitmap indexes are greatest for columns in which the ratio of the number of distinct values to the number of rows in the table is under 1%. We refer to this ratio as the degree of cardinality. A gender column, which has only two distinct values (male and female), is ideal for a bitmap index. However, data warehouse administrators also build bitmap indexes on columns with higher cardinalities.

For example, on a table with one million rows, a column with 10,000 distinct values is a candidate for a bitmap index. A bitmap index on this column can outperform a B-tree index, particularly when this column is often queried in conjunction with other indexed columns. In fact, in a typical data warehouse environments, a bitmap index can be considered for any non-unique column.

B-tree indexes are most effective for high-cardinality data: that is, for data with many possible values, such as customer_name or phone_number. In a data warehouse, B-tree indexes should be used only for unique columns or other columns with very high cardinalities (that is, columns that are almost unique). The majority of indexes in a data warehouse should be bitmap indexes.

In ad hoc queries and similar situations, bitmap indexes can dramatically improve query performance. AND and OR conditions in the WHERE clause of a query can be resolved quickly by performing the corresponding Boolean operations directly on the bitmaps before converting the resulting bitmap to rowids. If the resulting number of rows is small, the query can be answered quickly without resorting to a full table scan.

Example 6-1 Bitmap Index The following shows a portion of a company's customers table.

SELECT cust_id, cust_gender, cust_marital_status, cust_income_level
FROM customers;

CUST_ID    C CUST_MARITAL_STATUS  CUST_INCOME_LEVEL
---------- - -------------------- ---------------------
...
        70 F                      D: 70,000 - 89,999
        80 F married              H: 150,000 - 169,999
        90 M single               H: 150,000 - 169,999
       100 F                      I: 170,000 - 189,999
       110 F married              C: 50,000 - 69,999
       120 M single               F: 110,000 - 129,999
       130 M                      J: 190,000 - 249,999
       140 M married              G: 130,000 - 149,999
...

Because cust_gender, cust_marital_status, and cust_income_level are all low-cardinality columns (there are only three possible values for marital status and region, two possible values for gender, and 12 for income level), bitmap indexes are ideal for these columns. Do not create a bitmap index on cust_id because this is a unique column. Instead, a unique B-tree index on this column provides the most efficient representation and retrieval.

Table 6-1 illustrates the bitmap index for the cust_gender column in this example. It consists of two separate bitmaps, one for gender. Table 6-1 Sample Bitmap Index :

	gender='M'	gender='F'
cust_id 70	0	1
cust_id 80	0	1
cust_id 90	1	0
cust_id 100	0	1
cust_id 110	0	1
cust_id 120	1	0
cust_id 130	1	0
cust_id 140	1	0

Each entry (or bit) in the bitmap corresponds to a single row of the customers table. The value of each bit depends upon the values of the corresponding row in the table. For instance, the bitmap cust_gender='F' contains a one as its first bit because the region is east in the first row of the customers table. The bitmap cust_gender='F' has a zero for its third bit because the gender of the third row is not F.

An analyst investigating demographic trends of the company's customers might ask, "How many of our married customers have an income level of G or H?" This corresponds to the following SQL query: SELECT COUNT(*) FROM customers WHERE cust_marital_status = 'married' AND cust_income_level IN ('H: 150,000 - 169,999', 'G: 130,000 - 149,999');

Bitmap indexes can efficiently process this query by merely counting the number of ones in the bitmap illustrated in Figure 6-1. The result set will be found by using bitmap or merge operations without the necessity of a conversion to rowids. To identify additional specific customer attributes that satisfy the criteria, use the resulting bitmap to access the table after a bitmap to rowid conversion. Figure 6-1 Executing a Query Using Bitmap Indexes Bitmap Indexes and Nulls

Unlike most other types of indexes, bitmap indexes include rows that have NULL values. Indexing of nulls can be useful for some types of SQL statements, such as queries with the aggregate function COUNT.

Example 6-2 Bitmap Index

SELECT COUNT(*) FROM customers WHERE cust_marital_status IS NULL; This query uses a bitmap index on cust_marital_status. Note that this query would not be able to use a B-tree index. SELECT COUNT(*) FROM employees; Any bitmap index can be used for this query because all table rows are indexed, including those that have NULL data. If nulls were not indexed, the optimizer would be able to use indexes only on columns with NOT NULL constraints.

Bitmap Indexes on Partitioned Tables You can create bitmap indexes on partitioned tables but they must be local to the partitioned table--they cannot be global indexes. (Global bitmap indexes are supported only on nonpartitioned tables). Bitmap indexes on partitioned tables must be local indexes. Bitmap Join Indexes

In addition to a bitmap index on a single table, you can create a bitmap join index, which is a bitmap index for the join of two or more tables. A bitmap join index is a space efficient way of reducing the volume of data that must be joined by performing restrictions in advance. For each value in a column of a table, a bitmap join index stores the rowids of corresponding rows in one or more other tables. In a data warehousing environment, the join condition is an equi-inner join between the primary key column or columns of the dimension tables and the foreign key column or columns in the fact table. Bitmap join indexes are much more efficient in storage than materialized join views, an alternative for materializing joins in advance. This is because the materialized join views do not compress the rowids of the fact tables.

Example 6-3 Bitmap Join Index: Example 1

Using the example in "Bitmap Index", create a bitmap join index with the following sales table:
SELECT time_id, cust_id, amount FROM sales;

TIME_ID   CUST_ID    AMOUNT
--------- ---------- ----------
01-JAN-98      29700       2291
01-JAN-98       3380        114
01-JAN-98      67830        553
01-JAN-98     179330          0
01-JAN-98     127520        195
01-JAN-98      33030        280
...

CREATE BITMAP INDEX sales_cust_gender_bjix ON sales(customers.cust_gender)
FROM sales, customers WHERE sales.cust_id = customers.cust_id LOCAL;

The following query shows how to use this bitmap join index and illustrates its bitmap pattern:

SELECT sales.time_id, customers.cust_gender, sales.amount
FROM sales, customers
WHERE sales.cust_id = customers.cust_id;

TIME_ID   C AMOUNT
--------- - ----------
01-JAN-98 M       2291
01-JAN-98 F        114
01-JAN-98 M        553
01-JAN-98 M          0
01-JAN-98 M        195
01-JAN-98 M        280
01-JAN-98 M         32
...
Table 6-2 illustrates the bitmap join index in this example:

Table 6-2 Sample Bitmap Join Index

	cust_gender='M'	cust_gender='F'
sales record 1	1	0
sales record 2	0	1
sales record 3	1	0
sales record 4	1	0
sales record 5	1	0
sales record 6	1	0
sales record 7	1	0

You can create other bitmap join indexes using more than one column or more than one table, as shown in these examples. Example 6-4 Bitmap Join Index: Example 2

You can create a bitmap join index on more than one column, as in the following example, which uses customers(gender, marital_status): CREATE BITMAP INDEX sales_cust_gender_ms_bjix ON sales(customers.cust_gender, customers.cust_marital_status) FROM sales, customers WHERE sales.cust_id = customers.cust_id LOCAL NOLOGGING;

Example 6-5 Bitmap Join Index: Example 3

You can create a bitmap join index on more than one table, as in the following, which uses customers(gender) and products(category): CREATE BITMAP INDEX sales_c_gender_p_cat_bjix ON sales(customers.cust_gender, products.prod_category)FROM sales, customers, products

Example 6-6 Bitmap Join Index: Example 4

You can create a bitmap join index on more than one table, in which the indexed column is joined to the indexed table by using another table. For example, we can build an index on countries.country_name, even though the countries table is not joined directly to the sales table. Instead, the countries table is joined to the customers table, which is joined to the sales table. This type of schema is commonly called a snowflake schema.

CREATE BITMAP INDEX sales_c_gender_p_cat_bjix ON sales(customers.cust_gender, products.prod_category) FROM sales, customers, products WHERE sales.cust_id = customers.cust_id AND sales.prod_id = products.prod_id LOCAL NOLOGGING; Bitmap Join Index Restrictions Join results must be stored, therefore, bitmap join indexes have the following restrictions:

Parallel DML is currently only supported on the fact table. Parallel DML on one of the participating dimension tables will mark the index as unusable.

Only one table can be updated concurrently by different transactions when using the bitmap join index.

No table can appear twice in the join.

You cannot create a bitmap join index on an index-organized table or a temporary table.

The columns in the index must all be columns of the dimension tables.

The dimension table join columns must be either primary key columns or have unique constraints.

If a dimension table has composite primary key, each column in the primary key must be part of the join.

Logical Versus Physical Design in Data Warehouses

Your organization has decided to build a data warehouse. You have defined the business requirements and agreed upon the scope of your application, and created a conceptual design. Now you need to translate your requirements into a system deliverable. To do so, you create the logical and physical design for the data warehouse. You then define:

The specific data content

Relationships within and between groups of data

The system environment supporting your data warehouse

The data transformations required

The frequency with which data is refreshed

The logical design is more conceptual and abstract than the physical design. In the logical design, you look at the logical relationships among the objects. In the physical design, you look at the most effective way of storing and retrieving the objects as well as handling them from a transportation and backup/recovery perspective.

Orient your design toward the needs of the end users. End users typically want to perform analysis and look at aggregated data, rather than at individual transactions. However, end users might not know what they need until they see it. In addition, a well-planned design allows for growth and changes as the needs of users change and evolve.

By beginning with the logical design, you focus on the information requirements and save the implementation details for later. Creating a Logical Design

A logical design is conceptual and abstract. You do not deal with the physical implementation details yet. You deal only with defining the types of information that you need.

One technique you can use to model your organization's logical information requirements is entity-relationship modeling. Entity-relationship modeling involves identifying the things of importance (entities), the properties of these things (attributes), and how they are related to one another (relationships).

The process of logical design involves arranging data into a series of logical relationships called entities and attributes. An entity represents a chunk of information. In relational databases, an entity often maps to a table. An attribute is a component of an entity that helps define the uniqueness of the entity. In relational databases, an attribute maps to a column.

To be sure that your data is consistent, you need to use unique identifiers. A unique identifier is something you add to tables so that you can differentiate between the same item when it appears in different places. In a physical design, this is usually a primary key.

While entity-relationship diagramming has traditionally been associated with highly normalized models such as OLTP applications, the technique is still useful for data warehouse design in the form of dimensional modeling. In dimensional modeling, instead of seeking to discover atomic units of information (such as entities and attributes) and all of the relationships between them, you identify which information belongs to a central fact table and which information belongs to its associated dimension tables. You identify business subjects or fields of data, define relationships between business subjects, and name the attributes for each subject.

Your logical design should result in (1) a set of entities and attributes corresponding to fact tables and dimension tables and (2) a model of operational data from your source into subject-oriented information in your target data warehouse schema.

Data Warehouse Architectures

Data warehouses and their architectures vary depending upon the specifics of an organization's situation. Three common architectures are:

Data Warehouse Architecture (Basic)

Data Warehouse Architecture (with a Staging Area)

Data Warehouse Architecture (with a Staging Area and Data Marts)
Data Warehouse Architecture (Basic) Figure 1 shows a simple architecture for a data warehouse. End users directly access data derived from several source systems through the data warehouse.
Figure 1 Architecture of a Data Warehouse

In Figure 1, the metadata and raw data of a traditional OLTP system is present, as is an additional type of data, summary data. Summaries are very valuable in data warehouses because they pre-compute long operations in advance. For example, a typical data warehouse query is to retrieve something like August sales. A summary in Oracle is called a materialized view.

Data Warehouse Architecture (with a Staging Area)

In Figure 1, you need to clean and process your operational data before putting it into the warehouse. You can do this programmatically, although most data warehouses use a staging area instead. A staging area simplifies building summaries and general warehouse management. Figure 1-3 illustrates this typical architecture.

Figure 2 Architecture of a Data Warehouse with a Staging Area

Data Warehouse Architecture (with a Staging Area and Data Marts) Although the architecture in Figure 2 is quite common, you may want to customize your warehouse's architecture for different groups within your organization. You can do this by adding data marts, which are systems designed for a particular line of business. Figure 3 illustrates an example where purchasing, sales, and inventories are separated. In this example, a financial analyst might want to analyze historical data for purchases and sales.

Figure 3 Architecture of a Data Warehouse with a Staging Area and Data Marts

ER Modelling

What is ER?

ER is a logical design technique that seeks to remove the redundancy in data. Imagine that we have a business that takes orders and sells products to customers. In the early days of computing (long before relational databases) when we first transferred this data to a computer, we probably captured the original paper order as a single fat record with many fields. Such a record could easily have been 1,000 bytes distributed across 50 fields. The line items of the order were probably represented as a repeating group of fields embedded in the master record. Having this data on the computer was very useful, but we quickly learned some basic lessons about storing and manipulating data. One of the lessons we learned was that data in this form was difficult to keep consistent because each record stood on its own. The customer's name and address appeared many times, because this data was repeated whenever a new order was taken. Inconsistencies in the data were rampant, because all of the instances of the customer address were independent, and updating the customer's address was a messy transaction.

Even in the early days, we learned to separate out the redundant data into distinct tables, such as a customer master and a product master -- but we paid a price. Our software systems for retrieving and manipulating the data became complex and inefficient because they required careful attention to the processing algorithms for linking these sets of tables together. We needed a database system that was very good at linking tables. This paved the way for the relational database revolution, where the database was devoted to just this task.

The relational database revolution bloomed in the mid 1980s. Most of us learned what a relational database was by reading Chris Date's seminal book on the subject, An Introduction to Relational Databases (Addison-Wesley), first published in the early 1980s. As we paged through Chris's book, we worked through all of his Parts, Suppliers, and Cities database examples. It didn't occur to most of us to ask whether the data was completely "normalized" or whether any of the tables could be "snowflaked," and Chris didn't develop these topics. In my opinion, Chris was trying to explain the more fundamental concepts of how to think about tables that were relationally joined. ER modeling and normalization were developed in later years as the industry shifted its attention to transaction processing.

The ER modeling technique is a discipline used to illuminate the microscopic relationships among data elements. The highest art form of ER modeling is to remove all redundancy in the data. This is immensely beneficial to transaction processing because transactions are made very simple and deterministic. The transaction of updating a customer's address may devolve to a single record lookup in a customer address master table. This lookup is controlled by a customer address key, which defines uniqueness of the customer address record and allows an indexed lookup that is extremely fast. It is safe to say that the success of transaction processing in relational databases is mostly due to the discipline of ER modeling.

However, in our zeal to make transaction processing efficient, we have lost sight of our original, most important goal. We have created databases that cannot be queried! Even our simple order-taking example creates a database of dozens of tables that are linked together by a bewildering spider web of joins. (See Figure 1, page 60.) All of us are familiar with the big chart on the wall of the IS database designer's cubicle. The ER model for the enterprise has hundreds of logical entities! High-end systems such as SAP have thousands of entities. Each of these entities usually turns into a physical table when the database is implemented. This situation is not just an annoyance, it is a showstopper:

End users cannot understand or remember an ER model. End users cannot navigate an ER model. There is no graphical user interface (GUI) that takes a general ER model and makes it usable by end users.

Software cannot usefully query a general ER model. Cost-based optimizers that attempt to do this are notorious for making the wrong choices, with disastrous consequences for performance.

Use of the ER modeling technique defeats the basic allure of data warehousing, namely intuitive and high-performance retrieval of data.

Ever since the beginning of the relational database revolution, IS shops have noticed this problem. Many of them that have tried to deliver data to end users have recognized the impossibility of presenting these immensely complex schemas to end users, and many of these IS shops have stepped back to attempt "simpler designs." I find it striking that these "simpler" designs all look very similar! Almost all of these simpler designs can be thought of as "dimensional." In a natural, almost unconscious way, hundreds of IS designers have returned to the roots of the original relational model because they know the database cannot be used unless it is packaged simply. It is probably accurate to say that this natural dimensional approach was not invented by any single person. It is an irresistible force in the design of databases that will always appear when the designer places understandability and performance as the highest goals.

Figure 1.

Source :Extract from Drawing the line between Dimensional Modelling and ER modelling echniques.

Business Objects

Q. What are the different tools in Business Objects 5.1? 
What’s new in BusinessObjects 5.1?
Although not a major release over BUSINESSOBJECTS 5.0, BUSINESSOBJECTS 5.1 has some important new features.

· Save as PDF
· Add hyperlinks to reports
· Zero Administration BusinessObjects

BUSINESSOBJECTS 5.1 can be installed in two ways:
• from INFOVIEW via an Internet browser
• from the product CD

Q. Explain the Reporting features in Business Objects reporting tool?
How do you access data sources?
BUSINESSOBJECTS lets you access your data through a graphical user interface. You need no technical knowledge of the underlying data structures to get the information you want. What you do need, however, is knowledge of your business.
To access a data source with BUSINESSOBJECTS, you build a data provider. The types of data providers supported in BUSINESSOBJECTS depends on whether you install BUSINESSOBJECTS from the installation CD or install BUSINESSOBJECTS via an Internet browser.

Building a More Powerful Query
The procedures described in the following sections enable you to build a more powerful query by controlling the data that your queries retrieve. You can:
• Define scope of analysis, which means that you retrieve data that you will later use for analysis in the report.
• Limit the query results to data that satisfies conditions.
• Sort data, for example alphabetically.
• Retrieve a specified number of rows of data.
• Eliminate duplicate rows of data from the query result.

Running a Query on a Different Universe
BUSINESSOBJECTS allows you to run a query on one universe and then run the same query on a different universe. By doing this, you can test your query on a pilot universe before applying it to your real data.
1. Open the report containing the query.
2. From the Data menu, choose View Data. The Data Manager dialog box opens.
3. Choose the query you want to use in the Data Providers list, then click the Definition tab.
4. Click the button to the right of the current universe name.
5. In the dialog box that appears, select the universe you want to use, then click OK.
6. Click the Results tab, then Refresh.
7. Click OK to close the Data Manager.

Applying Groups of Conditions
You use conditions to limit the data retrieved by queries. A group of conditions consists of two or more conditions (predefined, simple or complex) applied on the same query. You use groups of conditions when a single condition does not enable you to obtain the data that you need.

A group of conditions consists of two or more conditions applied on the same query. In the Conditions box in the Query Panel, conditions are linked by an operator (AND or OR).
Building Combined Queries
BUSINESSOBJECTS lets you combine the data returned by up to eight queries as one set of results. These combined queries enable you to:
• Obtain a single column of data from multiple objects.
• Obtain data common to two sets of results, such as customers from a given region and a given age group.
• Exclude the results of one query from the results of another.
Note: Building combined queries allows you to combine or exclude data from the query result by using operators to combine the results of multiple queries. You can contrast this with using the In list and Not in list operators when you apply a complex condition on a query. The In list and Not in list operators include or exclude data from a query result based on a list of values that you enter.
Operators used to combine queries are Union, Intersection and Minus.
Setting up hierarchies for drill mode
Drill mode enables you to analyze data on different levels of detail. You perform analysis by navigating up, down and across hierarchies of data in a report. You drill down on the data to examine the details of more consolidated data. You drill up on data to examine totals for the underlying data. Your ability to drill on data requires that the data be organized into hierarchies.

Note: You can only work in drill mode if you have installed the EXPLORER option with BUSINESSOBJECTS.
Exporting Data From BusinessObjects

What external formats are available?
You can export data from BUSINESSOBJECTS to the following formats:
• Text. You can open the text file in many different applications, and on platforms other than Windows 
  (Macintosh, OS/2 or UNIX, for example).
• Spreadsheet format (Microsoft Excel). When you view the exported data in the spreadsheet application, 
  each value appears in a separate cell.
• RDBMS format (including .dbf format for dBASE). When you export data from BUSINESSOBJECTS to 
  RDBMS format, you create a relational table in the database. The table contains the columns of data  
  returned by the data provider. This feature enables you to extract a subset of data from a very large table,
  then export the result to your RDBMS. Once exported, the data can be retrieved by running a data  
  provider in BUSINESSOBJECTS. The universe designer can build a new universe, or edit an existing 
  universe, to map to the data in the new table. Alternatively, you can access the data directly by using free-
  hand SQL.
Options available to export data from BO
· Export to Local File format
· Export to RDBMS
· Copy to DDE
Using offline mode
Using BUSINESSOBJECTS in offline mode means that you are not connected to a repository which in turn means that, whatever your connection type, you will not be able to retrieve and send documents using BROADCAST AGENT. However, what you can do once you have opened BUSINESSOBJECTS in offline mode depends on the type of connection you chose to use in offline mode.
Client/Server connection
If you are using a BUSINESSOBJECTS client/server connection offline and not connected to a repository, you can still work with documents and universes stored locally on your computer and even create and refresh documents if you have a connection to the database, and the database connection and security information is stored on your computer.
Web connection
If you are using a web connection offline, you will not be able to retrieve documents from, and send documents to, Personal Document folders on the web server, and will not be able to create queries or refresh documents because all the database and connection information is stored on the web server.
In offline mode, you can continue to work on documents stored locally; you can work on the formatting of your reports or analyze data in existing reports, for example, and work with the data contained in the document to build new reports. If BUSINESSOBJECTS cannot establish the connection you requested with the web server, it may give you the option of starting BUSINESSOBJECTS in offline mode if your user rights allow you to work offline.
No remote connection
You may also choose to start BUSINESSOBJECTS in offline mode because you know you have no remote connection at all - for example, on a plane - and want to continue to work on documents you have stored locally. Note: The right to use BUSINESSOBJECTS offline is given to you by your BUSINESSOBJECTS supervisor or system administrator. Depending on how BUSINESSOBJECTS has been set up in your company, you may not even have the option of logging on to BUSINESSOBJECTS in offline mode.
Different ways of refreshing documents
BUSINESSOBJECTS allows you to refresh documents in the following ways:
• Manually
• Automatically at specific times or intervals
• By sending the document to Broadcast Agent, the BUSINESSOBJECTS product that manages the scheduled 
   processing of documents.
• Every time you open a document.

Saving a document for all users
If you want to make a document accessible to another user working without a repository, then check the Save for all users option in the Save as dialog box (Save As command, File menu). If you do not do this, users working without a repository will get an error message saying “You are not authorized to use this document” when they try to open your document. This is important to bear in mind if you are sending documents to other users via email, for example.
.

Displaying Data in Tables
BUSINESSOBJECTS has three basic ways of displaying the data in a report. You can display data in tables, in charts or in free-standing cells.
What are master/detail reports?
Master/detail reports enable you to split large blocks of data into sections. This type of presentation allows you to avoid repeating values and also to display subtotals.
Structuring a Master/Detail Report
You set up a master/detail report by setting a variable as a master cell. This section describes the different ways to do this. You can: 
• use a variable in a table or crosstab to create a master cell
• add a variable from the Report Manager to create a master cell


Organizing Data in Reports
Limiting the Data Displayed
You may not want to display all the data returned by a data provider in a report. You may want to focus on a selection of it only, which is difficult to do if there is a lot of data on the screen. A filter enables you to hide the data you do not want to view behind the scenes and display only the data you need. There are two types of filter. A global filter affects the whole report. A blockspecific filter only filters data for the specified chart, table or crosstab.
Creating more complex filters
Simple filters enable you to view only the data you need in a report. When you apply a simple filter, all you do is select values for a variable in the report. Complex filters enable you to display values that satisfy conditions. You define a complex filter by writing a formula.
Ignoring filters
You can force BUSINESSOBJECTS to ignore any filters you have inserted on a report so that when you make a calculation, the calculation is made on all the data, not just the filtered values. To do this, you use the 
NoFilter function. The syntax is: =NoFilter(formula)
Using Ranking to View the Top and Bottom Values
You may only want to show the extreme ranges of the data. For example, you may want to determine your top ten customers. Ranking enables you to look at the largest numbers and the smallest numbers in a report. Like filtering, it hides the data you do not want to display. The hidden data is not deleted from the report - you can view it again whenever you like by removing the ranking. Ranking also sorts the data in descending order. Thus, the largest value of the ranking is always at the top of the ranked column and the smallest value at the bottom. You can rank data contained in tables, crosstabs or master cells in master/detail reports.
Highlighting Data: using Alerter Note: You cannot use alerters on charts.
BUSINESSOBJECTS has standard calculation functions that enable you to make quick calculations on the data in reports. These calculations are available directly from a menu. The most commonly used calculations are also available on the Report toolbar.  
Understanding input and output contexts
BUSINESSOBJECTS defines an input context and an output context to determine the result of an aggregate calculation. Remember that a context is made up of one or more dimensions. The following table defines which dimensions in a report make up which context:
 
Analyzing Data in drill mode
What is drill mode?
Drill mode is a BOs analysis mode that allows you to break down data and view it from different angles and on different levels of detail to discover what is the driving factor behind a good or bad result.
Hierarchies
Objects are also organized in this way for drilling. When you analyze data in drill mode, you use hierarchies. The Universe classes are the default hierarchies you use for drilling but the Universe designer can also set up custom hierarchies. You can also create and edit hierarchies in your reports. Drill hierarchies only contain dimension objects. In drill mode, you drill down on dimensions, for example from Year to Quarter to Month. At each level, measures, such as Revenue or Profit Margin, are recalculated.
Qualifying Data For Hierarchies
BUSINESSOBJECTS qualifies data as dimensions, measures or details. Hierarchies only contain dimensions so if you want to include an object in a hierarchy for analysis in drill mode, you must qualify it as a dimension.   Note: You cannot change the qualification of data returned by a query on a universe.
Q.  What is Slice and Dice feature in Business Objects? 
                    Working in Slice-and-Dice Mode
Slice-and-dice mode enables you to switch the position of data in a report. You can, for ex, move data from columns to rows. The result would be a crosstab, where numeric data such as revenue appears at the intersection of rows and columns. You can also use slice-and-dice mode to:
• Work with master/detail reports                  • Display and remove data
• Rename, reset and delete blocks                  • Turn tables and crosstabs into charts, and vice versa
• Apply, edit and delete breaks, filters, sorts, rankings and calculations. 
Slice-and-dice mode is enabled by   the Slice and Dice Panel, a pop-up window that provides a graphical representation of the report you are   working on. You carry out tasks by dragging and dropping icons that represent the data you can use.
Formatting Sections
What are sections?
There are two types of section in a BUSINESSOBJECTS report.
Main Section
If you have not created any sections, the main section is the only section in the report and when you apply shading, the whole report (except margins) will be shaded in the same color.
Sections in a Master/Detail report
If you have set up a report with sections, you can apply a different type of shading to each section in the report. This can allow you to easily distinguish between the different sections. The sections you have created are contained in the main section and a main section header is displayed at the beginning of the report and a main section footer at the end of the report. You can hide the main section header or the main section footer or both of them if you wish.

Formatting Tables
Tables and crosstabs are made up of headers and footers, columns and rows, and cells. All these elements together make up the block. The cell is the most basic element of a table or crosstab. Rows and columns are made up of groups of cells. When you format tables and crosstabs, you can work on the formatting cell by cell or on the block formatting.
Using hyperlinks in BusinessObjects reports
You can easily add hyperlinks such as email addresses and web site addresses to your reports. BUSINESSOBJECTS automatically recognizes certain keywords or symbols included in the address, adds any extra syntax behind the scenes and formats the address as a hyperlink. Hyperlinks you add to a BUSINESSOBJECTS report are retained when you save the report in PDF or in HTML format.

Positioning report components
Relative positioning
Relative positioning means positioning a selected block in relation to markers such as page margins or other blocks. If these markers change in size or position the block is re-positioned accordingly. 
Using Outline View
When you have a report in sections with a lot of information in each section, a convenient way of presenting the report is to use outline view. Outline view folds up the sections in the report to display only the high level information that you’ve included at the top of each section. People viewing your reports can then open up the sections they are interested in to get more details. A bar with arrows is displayed at the left side of the report window. The number of buttons displayed at the bottom of the outline bar depends on the number of sections you have in the report.

What is a template?
A standard report does not contain information on page setup or include custom elements such as graphics. A BUSINESSOBJECTS template allows you to do this. A template is a special kind of BUSINESSOBJECTS document that contains pre-defined styles and structure that you use as a foundation to create reports. BUSINESSOBJECTS comes with several templates for you to use and you can also create your own.
Structure: The structure of a report defines how the data is presented. Your data can be presented in a crosstab, a column chart, or it can have a master/detail structure
Styles: The styles contained in a template define the report page background and the style of the headers and footers.