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Tasks done by INFORMATICA SERVER are:

a) Managing the sessions
b) Running the workflows
c) Tuning performance
d) Scheduling of sessions and workflows.

Tasks done by Informatica server are:

a) Managing the sessions
b) Running the workflows
c) Tuning performance
d) Scheduling of sessions and workflows.

The steps to copy MAPPING are MENTIONED below: 1.) First, open navigator WINDOW 2.) Open the mapping in repository 3.) Click copy

The steps to copy mapping are mentioned below: 1.) First, open navigator window 2.) Open the mapping in repository 3.) Click copy

These are shell COMMANDS that INFORMATICA server performs before running the session. We should have PERMISSION and privileges to RUN the options in Informatica.

These are shell commands that Informatica server performs before running the session. We should have permission and privileges to run the options in Informatica.

We can JOIN the tables USING LOOKUP tansformation and making a cartesian PRODUCT.

We can join the tables using lookup tansformation and making a cartesian product.

In case of DYNAMIC cache, when we are inserting a new ROW it checks the LOOKUP cache to see if it EXISTS, if not inserts it into the target as well as the cache but in case of static cache the new row is written only in the target and not the lookup cache. The lookup cache remains static and does not change during the session but INCASE of dynamic cache the server inserts, updates in the cache during session.

In case of dynamic cache, when we are inserting a new row it checks the lookup cache to see if it exists, if not inserts it into the target as well as the cache but in case of static cache the new row is written only in the target and not the lookup cache. The lookup cache remains static and does not change during the session but incase of dynamic cache the server inserts, updates in the cache during session.

They EXECUTE a SET of CODES WITHIN the LOOP and endloop.

They execute a set of codes within the loop and endloop.

An active TRANSFORMATION can CHANGE the number of rows that PASS through it, but a passive transformation can not change the number of rows that pass through it.

An active transformation can change the number of rows that pass through it, but a passive transformation can not change the number of rows that pass through it.

Various types of transformation are: Aggregator Transformation, Expression Transformation, Filter
Transformation, Joiner Transformation, Lookup Transformation, Normalizer Transformation, Rank Transformation,
ROUTER Transformation, Sequence Generator Transformation, STORED Procedure Transformation, Sorter
Transformation, Update STRATEGY Transformation, XML Source Qualifier Transformation, Advanced EXTERNAL
Procedure Transformation, External Transformation.

Various types of transformation are: Aggregator Transformation, Expression Transformation, Filter
Transformation, Joiner Transformation, Lookup Transformation, Normalizer Transformation, Rank Transformation,
Router Transformation, Sequence Generator Transformation, Stored Procedure Transformation, Sorter
Transformation, Update Strategy Transformation, XML Source Qualifier Transformation, Advanced External
Procedure Transformation, External Transformation.

Within a session. When you configure a session, you can instruct the Informatica SERVER to either TREAT all records in the same way (for EXAMPLE, treat all records as inserts), or use instructions coded into the session mapping to flag records for different database operations. Within a mapping. Within a mapping, you use the UPDATE Strategy transformation to flag records for insert, delete, update, or REJECT.

Within a session. When you configure a session, you can instruct the Informatica Server to either treat all records in the same way (for example, treat all records as inserts), or use instructions coded into the session mapping to flag records for different database operations. Within a mapping. Within a mapping, you use the Update Strategy transformation to flag records for insert, delete, update, or reject.

This transformation is used to MAINTAIN the history DATA or just most RECENT changes in to TARGET table.

This transformation is used to maintain the history data or just most recent changes in to target table.

Two SOURCES should have primary and FOREIGN KEY relationships. Two sources should have matching DATA TYPES.

Two sources should have primary and foreign key relationships. Two sources should have matching data types.

Tracing LEVELS STORE information about MAPPING and transformations.

Tracing levels store information about mapping and transformations.

NORMALIZER TRANSFORMATION.

Normalizer Transformation.

INSERT
DELETE
UPDATE
Update as update
Update as insert
Update ELSE insert
TRUNCATE table

Insert
Delete
Update
Update as update
Update as insert
Update else insert
Truncate table

INNER EQUI JOIN.

Inner equi join.

Whenever a session is CREATED for a mapping Aggregate Transformation, the session option for Incremental Aggregation can be enabled. When PowerCenter PERFORMS incremental aggregation, it passes new source DATA through the mapping and uses historical cache data to PERFORM new aggregation CALCULATIONS incrementally.

Whenever a session is created for a mapping Aggregate Transformation, the session option for Incremental Aggregation can be enabled. When PowerCenter performs incremental aggregation, it passes new source data through the mapping and uses historical cache data to perform new aggregation calculations incrementally.

JOINER transformation compares each row of the master source against the detail source. The fewer unique rows in the master, the fewer ITERATIONS of the join comparison OCCUR, which SPEEDS the join process.

Joiner transformation compares each row of the master source against the detail source. The fewer unique rows in the master, the fewer iterations of the join comparison occur, which speeds the join process.

Constraint based LOADING. the data was LOADED into the TARGET table based on the Constraints.i.e if we want to LOAD the EMP&DEPT data, first it loads the data of DEPT then EMP because DEPT is PARENT table EMP is CHILD table. In simple terms, it loads PARENT table first then CHILD table.

Constraint based loading. the data was loaded into the target table based on the Constraints.i.e if we want to load the EMP&DEPT data, first it loads the data of DEPT then EMP because DEPT is PARENT table EMP is CHILD table. In simple terms, it loads PARENT table first then CHILD table.

Abort can be used to Abort / stop the SESSION on an error condition. If the primary key COLUMN contains NULL, and you need to stop the session from continuing then you MAY use ABORT function in the DEFAULT value for the port. It can be used with IIF and DECODE function to Abort the session.

Abort can be used to Abort / stop the session on an error condition. If the primary key column contains NULL, and you need to stop the session from continuing then you may use ABORT function in the default value for the port. It can be used with IIF and DECODE function to Abort the session.

SELECT PROPERTIES, and then CLICK the Headers/Footers TAB.

Select Properties, and then click the Headers/Footers tab.

COGNOS Powerhouse is High-PRODUCTIVITY Application Development Solutions EQUIPS you with high-productivity development environments for creating your data-driven business solutions faster,whether for Web-based, client/server, or traditional terminal-based access. PowerHouse has GAINED a worldwide reputation for productivity, reliability, PERFORMANCE, and flexibility.

Cognos Powerhouse is High-Productivity Application Development Solutions equips you with high-productivity development environments for creating your data-driven business solutions faster,whether for Web-based, client/server, or traditional terminal-based access. PowerHouse has gained a worldwide reputation for productivity, reliability, performance, and flexibility.

MACRO-A macro is a set of instructions that can run applications.Example : A macro can OPEN your catalog,select a report(SAY for instance) convert that to another format and export it to any specified location,PROVIDED the code (Program)is such.Prompt-A prompt specifies the manner in which data in the reports are to be displayed.A Prompt can be defined at the catalog level either or during report GENERATION.

Macro-A macro is a set of instructions that can run applications.Example : A macro can open your catalog,select a report(say for instance) convert that to another format and export it to any specified location,provided the code (Program)is such.Prompt-A prompt specifies the manner in which data in the reports are to be displayed.A Prompt can be defined at the catalog level either or during report generation.

Add a list footer and a text messsage inside "No DATA". create a booloean conditional variable "Test" with code "rownum()>0". Select the complete list footer and set STYLE Variable, if Yes, Box Type of the List footer should be set to "NONE". This should work...RD.

Add a list footer and a text messsage inside "No Data". create a booloean conditional variable "Test" with code "rownum()>0". Select the complete list footer and set Style Variable, if Yes, Box Type of the List footer should be set to "none". This should work...RD.

The JUNK DIMENSION is simply a structure that provides a CONVENIENT place to STORE the junk attributes.

The junk dimension is simply a structure that provides a convenient place to store the junk attributes.

A catalog is a file containing the information (Database TABLES) that IMPROMPTU users need to CREATE reports.

► personal
► distributed
► shared
► SECURED

shared catalog is BETTER.

A catalog is a file containing the information (Database tables) that Impromptu users need to create reports.

► personal
► distributed
► shared
► secured

shared catalog is better.

It contains the miscellaneous ATTRIBUTES such as flags , which does belong to the main dimension table.

for eg; In a sales order fact table ,some informations LIKE, web-order , whether this is a ONLINE order or not new_cust , Is this PERSON a new CUSTOMER ?
verification , whether the order has been verified?

It contains the miscellaneous attributes such as flags , which does belong to the main dimension table.

for eg; In a sales order fact table ,some informations like, web-order , whether this is a online order or not new_cust , Is this person a new customer ?
verification , whether the order has been verified?

Cascading report WORKS BASED on the condition but drill THRU WORK based on the data item what we select as a drill thru options.

Cascading report works based on the condition but drill thru work based on the data item what we select as a drill thru options.

Drilling LETS you quickly move from one level of detail to ANOTHER to explore different aspects of your business. Drilling down moves you down in the hierarchy; drilling up moves you up in the hierarchy.

Slicing and Dicing:
While you can drill to look at information at any level, you can slice and DICE to SELECT the exact information you want in your report.

Drilling lets you quickly move from one level of detail to another to explore different aspects of your business. Drilling down moves you down in the hierarchy; drilling up moves you up in the hierarchy.

Slicing and Dicing:
While you can drill to look at information at any level, you can slice and dice to select the exact information you want in your report.

Semi-Additive: Semi-additive facts are facts that can be summed up for some of the dimensions in the fact table, but not the others. Non-Additive: Non-additive facts are facts that cannot be summed up for any of the dimensions present in the fact table. Current Balance and Profit MARGIN are the facts.Current Balance is a semi-additive fact, as it makes sense to add them up for all ACCOUNTS (what's the total current balance for all accounts in the bank?), but it does not make sense to add them up through time (ADDING up all current balances for a given account for each day of the month does not give US any useful information). Profit Margin is a non-additive fact, for it does not make sense to add them up for the account level or the day level.

Semi-Additive: Semi-additive facts are facts that can be summed up for some of the dimensions in the fact table, but not the others. Non-Additive: Non-additive facts are facts that cannot be summed up for any of the dimensions present in the fact table. Current Balance and Profit Margin are the facts.Current Balance is a semi-additive fact, as it makes sense to add them up for all accounts (what's the total current balance for all accounts in the bank?), but it does not make sense to add them up through time (adding up all current balances for a given account for each day of the month does not give us any useful information). Profit Margin is a non-additive fact, for it does not make sense to add them up for the account level or the day level.

go to tran FORMER,
build the cube
RIGHT click on the cube and OPEN PROPERTIES
go to drill through tab and select your report from that BROWSE option

go to tran former,
build the cube
right click on the cube and open properties
go to drill through tab and select your report from that browse option

Big Organizations have a lot of diversified SOURCES of data.There might be a dataware HOUSE exclusively for transport and others for data related to the project the company runs.In such case the complete enterprise's(company's) DATE WARE house is a big combination of all and is known the Enterprise data WAREHOUSE(EDW)

Big Organizations have a lot of diversified sources of data.There might be a dataware house exclusively for transport and others for data related to the project the company runs.In such case the complete enterprise's(company's) date ware house is a big combination of all and is known the Enterprise data Warehouse(EDW)

Alternate drill down path means there will be TWO path to opt.For EXAMPLE- We will have time DIMENSION now the client REQUIREMENT is they want two type of YEAR -one is calender year(Jan-Dec) and another is fiscal year(Apr-Mar).

Alternate drill down path means there will be two path to opt.For example- We will have time dimension now the client requirement is they want two type of year -one is calender year(Jan-Dec) and another is fiscal year(Apr-Mar).

You can create measure once you IMPORT all the DATA into the data SOURCE.You can create measures and dimensions by draging the required source from datasource into DIMENSION MAP and measure tab.(need to find scope of measures for all the dimensions)

You can create measure once you import all the data into the data source.You can create measures and dimensions by draging the required source from datasource into dimension map and measure tab.(need to find scope of measures for all the dimensions)

LOOP: loop is a closed PATH (relation) that exists among 3 (or) more tables. For EXAMPLE, if we have '3' tables T1, T2, T3 then, a loop exists among these tables only when we create joins in the following fashion:

Loop: T1 ---> T2 ---> T3 ---> T1

To resolve the above problem, we have to create a shortcut (or) ALIAS to the Table T1.

No Loop: T1 ---> T2 ---> T3 ---> Alias (or) Shortcut of T1

Loop: loop is a closed path (relation) that exists among 3 (or) more tables. For example, if we have '3' tables T1, T2, T3 then, a loop exists among these tables only when we create joins in the following fashion:

Loop: T1 ---> T2 ---> T3 ---> T1

To resolve the above problem, we have to create a shortcut (or) Alias to the Table T1.

No Loop: T1 ---> T2 ---> T3 ---> Alias (or) Shortcut of T1

Drill across means when you are MOVING from one report to ANOTHER report like country in one report and States in another Report WHEREAS if the report is using same report from moving from country to STATE. In other when you are moving details LEVEL if you are using the different report it is drill across and if you are using same report it is drill through.

Drill across means when you are moving from one report to another report like country in one report and States in another Report whereas if the report is using same report from moving from country to state. In other when you are moving details level if you are using the different report it is drill across and if you are using same report it is drill through.

PowerplayFrom format menu-->title, HEADER & FOOTER-->title-->insert report FILENAME

PowerplayFrom format menu-->title, header & footer-->title-->insert report filename

Visualizer is a representation of data CUBES in a dashboard format. We can drill through to the ground level of a hierarchy as like in POWER PLAY report but cannot add or remove fields dynamically.

Cognos script editor : We can WRITE cognos macros or programs in this TOOL and can fine tune or process some execution.

Visualizer is a representation of data cubes in a dashboard format. We can drill through to the ground level of a hierarchy as like in power play report but cannot add or remove fields dynamically.

Cognos script editor : We can write cognos macros or programs in this tool and can fine tune or process some execution.

IMPROMPTU menu GO to Catlog->User profiles -> userclass tab -> CLICK on Creator ->u can give there FOLDER access,table access,FILTERS,Governor etc

you can crate users by using USERS PROFILE option......and you can give permissions using ROLE IN C8 and GOVERNERS in C7

impromptu menu go to Catlog->User profiles -> userclass tab -> click on Creator ->u can give there folder access,table access,filters,Governor etc

you can crate users by using USERS PROFILE option......and you can give permissions using ROLE IN C8 and GOVERNERS in C7

By using Cognos Schedular, ONE can schedule the running REPORTS in IMPROMPTU to EXECUTE and save it in desired format.

By using Cognos MACRO script language the reports can be executed and distributed to recipients by using mail applications.

By using Cognos Schedular, one can schedule the running reports in Impromptu to execute and save it in desired format.

By using Cognos MACRO script language the reports can be executed and distributed to recipients by using mail applications.

In cognos report net by the validate report option a report can be tested. If there will be any error, it will specify the the error, unless it will GIVE message -'report specification is VALID'.

After creating the report we will connect to the ORACLE and we will write the SQL query and we will compare this 2 reports .

In cognos report net by the validate report option a report can be tested. If there will be any error, it will specify the the error, unless it will give message -'report specification is valid'.

After creating the report we will connect to the oracle and we will write the sql query and we will compare this 2 reports .

Cognos 6.6 7.0,7.3(PowerPlay, IMPROMPTU)--ReportNet1.0,1.1mr1, 1.1mr22---ReportNet 8.0(latest)IWR is use by Impromptu to publish reports, PPES is used by PP, Cognos CONNECTION is used by repornet. there are many other TOOLS but these are the main.

Cognos 6.6 7.0,7.3(PowerPlay, Impromptu)--ReportNet1.0,1.1mr1, 1.1mr22---ReportNet 8.0(latest)IWR is use by Impromptu to publish reports, PPES is used by PP, Cognos Connection is used by repornet. there are many other tools but these are the main.

The following are the stages of data warehousing:

Offline OPERATIONAL Database: It is the stage where copying the data off an operational system to another server where the report processing load against the copied data takes PLACE and OS performance does not impact.

Offline Data Warehouse: In this stage, data warehouses are updated from data in the OS and the data of data warehouse is stored in a data structure that is designed for facilitating reports.

Real time Data Warehouse: The data warehouses are updated often when an OS PERFORMS a transaction.

Integrated Data Warehouse: The data warehouses are updated by OS, at the time of performing a transaction. Then transactions are generated which are passed back into the operational SYSTEMS.

The following are the stages of data warehousing:

Offline Operational Database: It is the stage where copying the data off an operational system to another server where the report processing load against the copied data takes place and OS performance does not impact.

Offline Data Warehouse: In this stage, data warehouses are updated from data in the OS and the data of data warehouse is stored in a data structure that is designed for facilitating reports.

Real time Data Warehouse: The data warehouses are updated often when an OS performs a transaction.

Integrated Data Warehouse: The data warehouses are updated by OS, at the time of performing a transaction. Then transactions are generated which are passed back into the operational systems.

In Chain Data REPLICATION, the non-official data set distributed among many disks provides for LOAD balancing among the servers within the data warehouse.

Blocks of data are spread across clusters and each cluster can contain a complete set of replicated data. Every data block in every cluster is a unique permutation of the data in other clusters.

When a disk fails then all the calls made to the data in that disk are REDIRECTED to the other disks when the data has been replicated.

At times replicas and disks are added online without having to move around the data in the EXISTING copy or AFFECT the arm movement of the disk.

In load balancing, Chain Data Replication has multiple servers within the data warehouse share data request processing since data already have replicas in each server disk.

In Chain Data Replication, the non-official data set distributed among many disks provides for load balancing among the servers within the data warehouse.

Blocks of data are spread across clusters and each cluster can contain a complete set of replicated data. Every data block in every cluster is a unique permutation of the data in other clusters.

When a disk fails then all the calls made to the data in that disk are redirected to the other disks when the data has been replicated.

At times replicas and disks are added online without having to move around the data in the existing copy or affect the arm movement of the disk.

In load balancing, Chain Data Replication has multiple servers within the data warehouse share data request processing since data already have replicas in each server disk.

CARDINALITY is the term used in DATABASE relations to denote the OCCURRENCES of data on either SIDE of the relation.
There are 3 basic types of cardinality:
High data cardinality:
Values of a data column are very uncommon.
e.g.: email ids and the user names

Normal data cardinality:
Values of a data column are somewhat uncommon but never unique.
e.g.: A data column containing LAST_NAME (there may be several entries of the same last name)

LOW data cardinality:
Values of a data column are very usual.
e.g.: flag statuses: 0/1

Cardinality is the term used in database relations to denote the occurrences of data on either side of the relation.
There are 3 basic types of cardinality:
High data cardinality:
Values of a data column are very uncommon.
e.g.: email ids and the user names

Normal data cardinality:
Values of a data column are somewhat uncommon but never unique.
e.g.: A data column containing LAST_NAME (there may be several entries of the same last name)

Low data cardinality:
Values of a data column are very usual.
e.g.: flag statuses: 0/1

SECURITY domain in BUSINESS objects is a domain containing all security INFORMATION like login CREDENTIALS etc. It checks for users and their privileges. This domain is a part of the repository that also manages access to documents and FUNCTIONALITIES of each user.

Security domain in business objects is a domain containing all security information like login credentials etc. It checks for users and their privileges. This domain is a part of the repository that also manages access to documents and functionalities of each user.

Batch processing can be used to schedule reports. Objects can be ALSO be used for batch processing. Batch processing can be used to also SELECT the objects to be processed. The batch can be run as a transaction in which if one PROCESS fails, the entire batch is rolled back or it can be run as a SERIES of jobs.

Batch processing can be used to schedule reports. Objects can be also be used for batch processing. Batch processing can be used to also select the objects to be processed. The batch can be run as a transaction in which if one process fails, the entire batch is rolled back or it can be run as a series of jobs.

Functional differences
• Business OBJECTS, for building or accessing REPORTS, needs to be installed on every pc. On the other hand, Web intelligence reports needs a browser and a URL of the server from where Business objects will be accessed.
• BOMain.key needs to be copied on every pc using BO client. This is not required for Web Intelligence Reports.
• Business objects expect you to use the same pc where they are installed. Web Intelligence reports can be accessed from anywhere, provided internet is available.

Architectural differences
For BO client, for sending info to BO Server BOMain.key, uses the key of the local drive. Once the information is SENT, it is validated and checked into the repository upon which the user can access the BO services. On the other hand, Web Intelligence the web servers BOMain.key is USED to check privilege of the user and then sending information to the BO Server BOMain.key.

Functional differences
• Business objects, for building or accessing reports, needs to be installed on every pc. On the other hand, Web intelligence reports needs a browser and a URL of the server from where Business objects will be accessed.
• BOMain.key needs to be copied on every pc using BO client. This is not required for Web Intelligence Reports.
• Business objects expect you to use the same pc where they are installed. Web Intelligence reports can be accessed from anywhere, provided internet is available.

Architectural differences
For BO client, for sending info to BO Server BOMain.key, uses the key of the local drive. Once the information is sent, it is validated and checked into the repository upon which the user can access the BO services. On the other hand, Web Intelligence the web servers BOMain.key is used to check privilege of the user and then sending information to the BO Server BOMain.key.

Security LEVEL used in BO:-
Row Level
COLUMN Level
Both the LEVELS are used to restrict data at a row or column level to a user or a group. Both the security levels are handled by the administrator of the tool.

Security level used in BO:-
Row Level
Column Level
Both the levels are used to restrict data at a row or column level to a user or a group. Both the security levels are handled by the administrator of the tool.

Object QUALIFICATION is an ATTRIBUTE of an object that helps to DETERMINE how it can be used in multidimensional analysis. Using this, the multidimensional analysis objects can EITHER be qualified as dimension, detailed and measure.

Object qualification is an attribute of an object that helps to determine how it can be used in multidimensional analysis. Using this, the multidimensional analysis objects can either be qualified as dimension, detailed and measure.

A BOMain.key FILE CONTAINS all relevant information about the repository. It contains the ADDRESS of the repository security domain. The file is sotred in the LOCData folder.

A BOMain.key file contains all relevant information about the repository. It contains the address of the repository security domain. The file is sotred in the LOCData folder.