With the exponential growth of data and the need for organizations to effectively manage and utilize their data assets, there is a high demand for professionals skilled in Informatica MDM. So, if you are attending an Informatica MDM interview, you should take a look at these commonly asked Informatica MDM Interview questions and answers.
If you're looking for Informatica MDM Interview Questions for Experienced or Freshers, you are in the right place. There are a lot of opportunities from many reputed companies in the world. According to research Informatica MDM has a market share of about 3.0%. So, You still have the opportunity to move ahead in your career in Informatica MDM Development. Mindmajix offers Advanced Informatica MDM Interview Questions 2023 that helps you in cracking your interview & acquire a dream career as Informatica MDM Developer.
10) What is OLTP?
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MDM stands for Master Data Management. It is a comprehensive method used to enable an enterprise for linking all of its critical data to a single file also known as a master file, providing a common point of reference. When done in a proper manner, MDM helps in streamlining the process of data sharing among departments and personnel.
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.
Data Warehousing is the main depot of an organization’s historical data and its corporate memory, containing the raw material for the decision support system of management. What lead to the use of data warehousing is that it allows a data analyst to execute complex queried and analyses like data mining on the info without making any slow in an operational system. The collection of data in Data warehousing is planned for supporting the decision making of the management. These warehouses contain an array of data presenting a coherent image of business conditions in time at a single point. Data Warehousing is a repository of information that is available for analysis and query.
There are two types of tables involved in Dimensional Modeling and this model concept is different from the third normal form. The Dimensional data model concept makes use of the facts table containing the measurements of the business and the dimension table containing the measurement context.
There are various fundamental stages of Data warehousing. They are:
Offline Operational Databases: This is the first stage in which data warehouses are developed simply by copying operational system databases to an offline server where dealing out a load of reporting not put any impact on the performance of the operational system.
Offline Data Warehouse: In this stage of development, data warehouses are updated on a regular basis from the operational systems. Plus, all the data is stored in an incorporated reporting-oriented data structure.
Real-Time Data Warehouse: During this stage, data warehouses are updated on an event or transaction basis. Also, an operational system executes a transaction every time.
Integrated Data Warehouse: This is the last stage where data warehouses are used for generating transactions or activity passing back into the operating system for the purpose of use in an organization's daily activity.
Designed by Informatica Corporation, Informatica PowerCenter 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.
There are various components of Informatica PowerCenter. They are as follows:
Mapping can be best described as a set of target definitions and sources connected with transformation objects defining data transformation rules. It represents the flow of data between targets and sources.
Mapplet is a reusable object containing a set of transformations and also allowing to reuse that transformation logic in a wide range of mappings.
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 a mapplet or mapping.
Data Mining is a process that helps in analyzing data from several perspectives and also allows summarizing it into helpful information.
The fact table is the process containing the measurement of business processes along with the foreign keys for dimension tables.
Dimension table is a compilation of categories, hierarchies, and logic which can further be used for the traverse purpose in hierarchy nodes. It includes textual attributes of measurements that are stored in fact tables.
Dimension Table’s foreign keys are the primary keys of entity tables. Fact Table’s foreign keys are primary keys of dimension tables
Two different methods are there for loading data in dimension tables. They are as follows:
Direct or fast: In this method, all the keys and constraints are disabled prior to loading the data. Once the complete data is loaded, it is legalized against all the keys and constraints. In case the data is found to be invalid then it will not be included in the index. Plus, all the future processed on this data is skipped.
Conventional or slow: In this method, all the keys and constraints are legalized prior to the data is loaded. In this way, it helps in maintaining data integrity.
There are a number of objects that you cannot use in a mapplet. They are:
The repository can be imported and exported to the new environment
Informatica deployment groups can be used
Folders/objects can be copied
Each mapping can be exported to xml and then be imported into a new environment
There are several ways for deleting duplicate records in Informatica. They are as follows:
Making use of select distinct in source qualifier
Making use of group and aggregator by all fields
By overriding SQL query in source qualifier
A Mapping variable is dynamic, i.e. it can vary anytime throughout the session. The variable’s initial value before the starting of the session is read by PowerCenter, which makes use of variable functions to change the value. And before the session ends, it saves the current value. However, the last value is held by the variable itself. The next time when the session runs, the value of the variable is the last saved value in the previous session.
A Mapping parameter is a static value, defined by you before the session starts and the value remains the same until the end of the session. Once the session runs, PowerCenter evaluates the parameter’s value and retains the same value during the entire session. Next time, when the session runs, it reads the value from the file.
There are various repositories that can be formed with the help of the Informatica Repository Manager. They are as follows:
Standalone Repository: It is a repository functioning individually as well as is not related to any other repositories.
Local Repository: This repository functions within a domain. It is able to connect to a global repository with the help of global shortcuts. Also, it can make use of objects in its shared folders.
Global Repository: This repository works as a centralized repository in a domain. It contains shared objects crossways the repositories in a domain.
By using a query all the invalid mappings in a folder can be found. It is:
SELECT MAPPING_NAME FROM REP_ALL_MAPPINGS WHERE SUBJECT_AREA='YOUR_FOLDER_NAME' AND PARENT_MAPPING_IS_VALIED <>1
A data movement mode helps in determining how the 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
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.
OLTP stands for Online Transaction Processing that helps in modifying data the example it receives as well as having a huge number of concurrent users.
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.
Two types of LOCK are used in Informatica MDM 10.1. They are:
Exclusive Lock: Letting just one user make alterations to the underlying operational reference store.
Write Lock: Letting multiple users make amendments to the underlying metadata at the same time.
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.
Merge managers, data managers, and hierarchy managers do not demand to write locks. Besides. The audit manager also does not need to write locks.
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There are several tools that require LOCK to make configuration changes to the database of MDM Hub Master. They are:
There are various tables that are linked with staging data in Informatica MDM. They are:
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Ravindra Savaram is a Technical Lead at Mindmajix.com. His passion lies in writing articles on the most popular IT platforms including Machine learning, DevOps, Data Science, Artificial Intelligence, RPA, Deep Learning, and so on. You can stay up to date on all these technologies by following him on LinkedIn and Twitter.
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