MDM basics interview questions and answers

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.

There are two types of table involved in Dimensional Modeling and this model concept is different from the third normal form. Dimensional data model concept makes use of facts table containing the measurements of the business and dimension table containing the measurement context.

A data movement mode determines how the 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

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 a new environment

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.

It is a repository object that helps in generating, modifying or passing data. In a mapping, transformations make a representation of the operations integrated with service performs on the data. All the data goes by transformation ports that are only linked with maple or mapping.

Foreign keys of dimension tables are the primary keys of entity tables.
Foreign keys of facts tables are the primary keys of dimension tables.
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A Mapplet is a reusable object that contains a set of transformations and enables to reuse that transformation logic in multiple mappings.

There are two different ways to load data in dimension tables.
Conventional (Slow) – All the constraints and keys are validated against the data before, it is loaded; this way data integrity is maintained.
Direct (Fast) – All the constraints and keys are disabled before the data is loaded. Once data is loaded, it is validated against all the constraints and keys. If data is found invalid or dirty it is not included in the index and all future processes are skipped on this data. (ALL Interview Questions)

Designed by Informatica Corporation, it is data integration software providing an environment that lets data loading into a centralized location like a data warehouse. From here, data can be easily extracted from an array of sources, also can be transformed as per the business logic and then can be easily loaded into files as well as relation targets.

This specifies the parallelism’s degree that is set upon the base object table as well as its related tables. Although it doesn’t occur for all batch processes, it can have a positive consequence on performance once it’s used. Nevertheless, its use is restricted by the number of CPUs on the database server machine along with the amount of available memory. 1 is the default value.

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

Dimensional data model concept involves two types of tables and it is different from the third normal form. This concept uses Facts table which contains the measurements of the business and Dimension table which contains the context (dimension of calculation) of the measurements.

A transformation is a repository object that generates, modifies or passes data. Transformations in a mapping represent the operations the Integration Service performs on the data. Data passes through transformation ports that are linked in a mapping or mapplet.

There are various components of Informatica PowerCenter. They are as follows:PowerCenter Repository
– PowerCenter Domain
– PowerCenter Client
– Administration Console
– Integration Service
– Repository Service
– Data Analyser
– Web Services Hub
– PowerCenter Repository Reports
– Metadata Manager

Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information.

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

Powercenter is data integration software of Informatica Corporation which provides an environment that allows loading 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.

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

 In every 60 seconds, the hub console is refreshed in the current connection. A lock can be released manually by a user. In case the user switches to another database while having a hold of a lock, then the lock will be released automatically. In case the hub console is terminated by the user, then the lock will be expired after a minute.

 A Mapping Parameter is a static value that you define before running the session and its value remains until 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.

– COBOL source definition
– Joiner transformations
– Normalizer transformations
– Non reusable sequence generator transformations.
– Pre or post-session stored procedures
– Target definitions
– Power mart 3.5 styles Look Up functions
– XML source definitions
– IBM MQ source definitions

OLAP is an abbreviation of Online Analytical Processing. This system is an application that collects, manages, processes and presents multidimensional data for analysis and management purposes.

There is always a challenge for technical folks in data governance to sell the project and get the fund. There is always a look for ROI by management. They require MDM knotted to quantifiable benefits that are considered by business leaders such as dollar amounts around ROI.

A data movement mode helps in determining how power center server takes care of the character data. Data movement is selected in the Informatica server configuration settings. There are two different data movement modes available in Informatica. They are:
-> ** Unicode Mode and ASCII Mode
-> ** Explain OLAP.
->** OLAP stands for Online Analytical Processing. It processes as an app helps that gathers, manages, presents and processes multidimensional data for management and analysis purposes.

In the source, qualifier use select distinctly, Use Aggregator and group by all fields, Override SQL query in Source qualifier