Explore topic-wise InterviewSolutions in .

DATA movement MODES determines how power center server handles the CHARACTER data. We CHOOSE the data movement in the INFORMATICA server configuration settings. Two types of data movement modes available in informatica.

• ASCII mode
• Unicode mode

Data movement modes determines how power center server handles the character data. We choose the data movement in the informatica server configuration settings. Two types of data movement modes available in informatica.

USE FOLLOWING query

SELECT MAPPING_NAME FROM REP_ALL_MAPPINGS WHERE 

SUBJECT_AREA='YOUR_FOLDER_NAME' AND PARENT_MAPPING_IS_VALIED <>1

Use following query

SELECT MAPPING_NAME FROM REP_ALL_MAPPINGS WHERE 

SUBJECT_AREA='YOUR_FOLDER_NAME' AND PARENT_MAPPING_IS_VALIED <>1

Standalone Repository : A repository which FUNCTIONS INDIVIDUALLY and is unrelated to any other repositories.

Global Repository : This is a centralized repository in a domain. This repository can contain shared OBJECTS across the repositories in a domain. The objects are shared through global shortcuts.

Local Repository : Local repository is WITHIN a domain . Local repository can CONNECT to a global repository using global shortcuts and can use objects in it’s shared folders.

Standalone Repository : A repository which functions individually and is unrelated to any other repositories.

Global Repository : This is a centralized repository in a domain. This repository can contain shared objects across the repositories in a domain. The objects are shared through global shortcuts.

Local Repository : Local repository is within a domain . Local repository can connect to a global repository using global shortcuts and can use objects in it’s shared folders.

Following are WAYS to remove duplicate records

• In source qualifier use select DISTINCT
• Use AGGREGATOR and group by all fields
• Override SQL query in Source qualifier

Following are ways to remove duplicate records

A Mapping parameter is a STATIC VALUE that you define before running the session and it value remains till the end of the session.when we run the session PowerCenter evaluates the value from the parameter and retains the same value throughout the session. When the session run again it READS from the file for its value.

A Mapping variable is dynamic or changes anytime during the session. PowerCenter reads the initial value of the variable before the start of the session and changes its value by using variable functions and before ending the session its saves the current value (LAST value held by the variable). Next time when the session runs the variable value is the last saved value in the previous session.

A Mapping parameter is a static value that you define before running the session and it value remains till the end of the session.when we run the session PowerCenter evaluates the value from the parameter and retains the same value throughout the session. When the session run again it reads from the file for its value.

A Mapping variable is dynamic or changes anytime during the session. PowerCenter reads the initial value of the variable before the start of the session and changes its value by using variable functions and before ending the session its saves the current value (last value held by the variable). Next time when the session runs the variable value is the last saved value in the previous session.

• We can export repository and IMPORT into the new environment
• We can use INFORMATICA DEPLOYMENT groups
• We can Copy folders/objects
• We can Export each MAPPING to XML and import in new environment

• COBOL source definition
• JOINER transformations
• NORMALIZER transformations
• Non reusable sequence generator transformations.
• PRE or post session stored PROCEDURES
• Target definitions
• Power mart 3.5 STYLE Look Up functions
• XML source definitions
• IBM MQ source definitions

Dimensional table contains textual ATTRIBUTES of MEASUREMENTS STORED in the FACTS tables. Dimensional table is a collection of hierarchies, CATEGORIES and logic which can be used for user to traverse in hierarchy nodes.

Dimensional table contains textual attributes of measurements stored in the facts tables. Dimensional table is a collection of hierarchies, categories and logic which can be used for user to traverse in hierarchy nodes.

• FOREIGN keys of DIMENSION TABLES are primary keys of entity tables.
• Foreign keys of FACTS tables are primary keys of Dimension tables.

AN mapplet is a REUSABLE OBJECT that CONTAINS a set of transformations and enables to REUSE that transformation logic in multiple mappings.

AN mapplet is a reusable object that contains a set of transformations and enables to reuse that transformation logic in multiple mappings.

A MAPPING is a SET of source and target definitions linked by TRANSFORMATION objects that define the rules for DATA transformation. Mappings represent the data flow between SOURCES and targets.

A mapping is a set of source and target definitions linked by transformation objects that define the rules for data transformation. Mappings represent the data flow between sources and targets.

Following are the various components of Informatica PowerCenter,

• PowerCentre Domain
• PowerCenter REPOSITORY
• Administration Console
• PowerCenter CLIENT
• Repository Service
• INTEGRATION service
• Web Services HUB
• Data Analyzer
• Metadata Manager
• PowerCenter Repository REPORTS

Following are the various components of Informatica PowerCenter,

Powercenter is DATA INTEGRATION software of Informatica Corporation which PROVIDES an environment that allows to LOAD data into a centralized location such as data warehouse. Data can be extracted from multiple sources can be transformed according to the business logic and can be loaded into files and RELATION targets.

Powercenter is data integration software of Informatica Corporation which provides an environment that allows to load data into a centralized location such as data warehouse. Data can be extracted from multiple sources can be transformed according to the business logic and can be loaded into files and relation targets.

Offline Operational Databases : DATA warehouses in this initial stage are developed by simply copying the database of an operational system to an off-line server where the processing LOAD of reporting does not impact on the operational system’s performance.

Offline Data Warehouse: Data warehouses in this stage of evolution are updated on a regular time cycle (usually daily, weekly or monthly) from the operational systems and the data is stored in an integrated reporting-oriented data structure.

Real Time Data Warehouse:Data warehouses at this stage are updated on a TRANSACTION or event basis, every time an operational system performs a transaction (e.g. an order or a delivery or a booking ETC.)

Integrated Data Warehouse : Data warehouses at this stage are used to generate activity or TRANSACTIONS that are passed back into the operational systems for use in the daily activity of the organization.

Offline Operational Databases : Data warehouses in this initial stage are developed by simply copying the database of an operational system to an off-line server where the processing load of reporting does not impact on the operational system’s performance.

Offline Data Warehouse: Data warehouses in this stage of evolution are updated on a regular time cycle (usually daily, weekly or monthly) from the operational systems and the data is stored in an integrated reporting-oriented data structure.

Real Time Data Warehouse:Data warehouses at this stage are updated on a transaction or event basis, every time an operational system performs a transaction (e.g. an order or a delivery or a booking etc.)

Integrated Data Warehouse : Data warehouses at this stage are used to generate activity or transactions that are passed back into the operational systems for use in the daily activity of the organization.

A data warehouse is the main repository of an ORGANIZATION’s HISTORICAL data, its corporate memory. It contains the raw material for management’s decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems. Data warehousing collection of data designed to support management decision making. Data warehouses CONTAIN a WIDE variety of data that present a coherent picture of business conditions at a single point in time. It is a repository of INTEGRATED information, available for queries and analysis.

A data warehouse is the main repository of an organization’s historical data, its corporate memory. It contains the raw material for management’s decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems. Data warehousing collection of data designed to support management decision making. Data warehouses contain a wide variety of data that present a coherent picture of business conditions at a single point in time. It is a repository of integrated information, available for queries and analysis.

Technical folks often have a challenge in data governance in selling the project and getting the FUNDING. Management is LOOKING for RETURN on investment; they need MDM tied to quantifiable benefits that business leaders understand, like dollar amounts around ROI.

Technical folks often have a challenge in data governance in selling the project and getting the funding. Management is looking for return on investment; they need MDM tied to quantifiable benefits that business leaders understand, like dollar amounts around ROI.

It’s a matter of AWARENESS and the problem becoming urgent. We are seeing budgets INCREASED and greater success in closing deals, particularly in the pharmaceutical and financial services industries. For rester predicts MDM will be $6 billion market by 2010, which is a 60-percent growth rate over the $1 billion MDM market last YEAR. Gartner forecasts that 70 percent of Global 2000 companies will have a MDM solution by the year 2010. These are pretty big numbers.

It’s a matter of awareness and the problem becoming urgent. We are seeing budgets increased and greater success in closing deals, particularly in the pharmaceutical and financial services industries. For rester predicts MDM will be $6 billion market by 2010, which is a 60-percent growth rate over the $1 billion MDM market last year. Gartner forecasts that 70 percent of Global 2000 companies will have a MDM solution by the year 2010. These are pretty big numbers.

There is huge AWARENESS of MDM. Gartner recently hosted a MDM conference for the first time [piggy-backing on its CRM conference], and they pulled in about 500 attendees.

As to whether they “GET it,” it depends on who you’re talking to. Most of the IT people get it. Business users understand the moniker, but they might or might not understand MDM QUITE as well. I find that business users often require education in terms of what it can do for them and what value it BRINGS. With IT people, it’s a different conversation; they want to know more about the features and how we differentiate ourselves from the COMPETITION.

There is huge awareness of MDM. Gartner recently hosted a MDM conference for the first time [piggy-backing on its CRM conference], and they pulled in about 500 attendees.

As to whether they “get it,” it depends on who you’re talking to. Most of the IT people get it. Business users understand the moniker, but they might or might not understand MDM quite as well. I find that business users often require education in terms of what it can do for them and what value it brings. With IT people, it’s a different conversation; they want to know more about the features and how we differentiate ourselves from the competition.

Master data management (MDM) is a comprehensive method of ENABLING an ENTERPRISE to link all of its critical data to ONE file, called a master file, that provides a common point of reference. When properly done, MDM streamlines data sharing among personnel and departments.

Master data management (MDM) is a comprehensive method of enabling an enterprise to link all of its critical data to one file, called a master file, that provides a common point of reference. When properly done, MDM streamlines data sharing among personnel and departments.