Informatica MDM Interview Questions and Answers

SLA Jobs offers both experienced and novice candidates a comprehensive set of Informatica MDM interview questions and answers. You can solve your Informatica MDM job interview with the help of this section of questions and answers. Check out our Informatica training syllabus that helps you get started with data warehousing concepts.

Describe MDM.

Master Data Management (MDM) is an integrated strategy that enables an organization to connect all of its vital data to a single file, known as a master file, which serves as a shared point of reference. Once properly completed, MDM streamlines data sharing across personnel and departments.

How do MDM’s match and merge functions work?

Match: Identifies probable duplicates by matching records to established criteria or rules. For example, two customer records that have very similar names and addresses may be considered a match.

Merge: After identifying duplicates, the records are integrated into a single, consolidated record. This procedure selects the best or most accurate information from each duplicate record to produce a “golden” or master record.

A landing table: what is it?

In MDM, a landing table is a temporary table that is filled with data from source systems. Before it is cleaned and processed, it contains the raw data. used to collect data initially before it is transformed or validated.

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A trust framework: what is it?

  • A collection of guidelines, norms, and standards was developed to assess the correctness and dependability of data sources in MDM.
  • It assesses and rates data according to its quality, recency, and source.
  • It helps in choosing the most important facts to consider while settling disputes during the merging process.

In MDM, what are lookup tables?

Lookup tables are reference tables that help throughout the purification process by converting source values to standardized values. tables that have reference information that is used to improve and support the processes of data enrichment and transformation. Include pre-made lists or mappings, like product numbers to product descriptions or nation codes to country names.

A cleansing function: what is it?

  • To guarantee the quality and consistency of data, an MDM cleanse function is utilized to adjust and standardize the data.
  • A procedure or method used in MDM (and other data management systems) to find, fix, and eliminate data errors and inconsistencies.
  • It can add extra information to data, fix typos, and standardize data formats.

What makes up MDM Hub’s components?

The Hub Console, Hub Store, Cleanse Match Servers, and Services Integration Framework are some of the parts that make up MDM Hub.

Hub Store: the central repository for data.

Hub Console: The management administration interface.

Cleanse Engine: Consistently verifies information.

Match Engine: Identifies redundant data.

Merge Manager: Combines redundant information.

Batch Data Process: Oversees the management of batch data activities.

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What do Informatica MDM base objects mean?

  • Customers and products are examples of fundamental entities in MDM that represent master data.
  • Keep the combined, filtered, and duplicate-free data.
  • acted as the main components needed to create an integrated data view in MDM.

SIF: What is it?

Applications developed by third parties can interface with Informatica MDM Hub through a set of application programming interfaces called the Services Integration Framework, or SIF for short. offers services and APIs for integrating MDM with third-party programs and systems. Permits synchronization, functionality extension, and real-time data access.

What is the difference between MDM and ETL?

The purpose of MDM is data consistency and accuracy, with a focus on master data. It integrates well with master data and its key activities are data modeling and governance. ETL, on the other hand, aims to provide data extraction and transformation. It focuses mainly on structured and unstructured data. ETL transforms data for analysis and its key activities are data extraction and loading. 

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What role does the ORS play in Informatica MDM?

The MDM data model resides in an Operational Reference Store (ORS). Landing tables, staging tables, and base objects are all included. Within the same MDM hub, it guarantees data segregation for several initiatives or projects. It contains the master data records that have been combined, cleaned, and deduplicated. 

Multiple ORSs, each devoted to a distinct master data collection or purpose (e.g., testing, development, or production), can exist within an organization. Versioning is supported, making it possible to monitor changes to previous data and offering an auditing tool.

Describe the Hub Console’s function.

Users of Informatica MDM can configure, manage, and keep an eye on MDM hub processes and components using the Hub Console user interface. Administrators set up and oversee the fundamental features of MDM here, including data modeling, batch operations, match and merge rules, and user roles and permissions.

Data stewards can analyze possible duplicates, oversee data quality operations, and decide whether to merge records using this console. It offers capabilities for monitoring job execution, importing and exporting information, and producing reports on operations and data quality.

How is information added to MDM?

Extraction: Data is extracted from the original systems.

Landing: Landing tables are originally filled with data.

Staging: For fundamental validation, data is moved to staging tables.

Cleaning: The Cleanse Engine is used to standardize and fix data.

Matching: Possibly redundant records are located.

Merging involves combining duplicates into master records.

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Stage Tables: What Are They?

Data that has been cleaned up and prepared for matching and merging is stored in staging tables. After preliminary processing and purification, data is transferred from landing tables to staging tables.

  • Used to load data from source systems to prepare it for future processing.
  • It makes it easier to do initial validation, transformation, and cleaning procedures.

Which different match kinds does Informatica MDM offer?

Exact Match: Finds records that have the same values.

Fuzzy Match: Identifies possible copies with minute differences.

Auto Match: Matching is automated using an algorithm called Auto Match.

Consolidation Match: Chooses the best version by grouping records.

Unduplicate Match: Examines duplicates that were previously flagged again.

Phonetic Match: Finds tracks that have comparable tones.

Describe the MDM Batch Viewer.

  • An Informatica MDM Hub Console component.
  • Offers a graphical user interface for batch job management and monitoring in the MDM system.
  • It enables users to examine batch job logs, statistics, and statuses for operations including load, match, combine, and cleanse.
  • Provides information about mistakes or problems that occur during batch processing, which aids in problem-solving.
  • Provides the ability to launch, pause, and resume particular batch operations as needed.

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In MDM, what is a composite key?

A record in a database table that may be uniquely identified by combining two or more properties or columns. To guarantee uniqueness and precise record identification, several attributes are integrated rather than depending only on one. It is particularly helpful in situations where a record cannot be uniquely identified by a single attribute.

How are disputes settled during the merger process?

The MDM’s trust and validation criteria serve as the basis for resolving conflicts that arise throughout the merger process. Data from the source system with the greatest trust score is often given priority.

Trust Scores: Sort data according to the dependability of the source.

Predefined Rules: Establish predetermined rules to determine which data is prioritized.

Rules for Survivorship: Choose the data characteristic that “survives” according to standards like recency.

Describe what Informatica MDM’s hierarchy management means.

Organizations may manage intricate relationships and hierarchies among data entities with Informatica MDM’s hierarchical management feature. Relationships like product hierarchies and organizational structures may fall under this category.

Organizational charts and product hierarchies, among other complicated data interactions and structures, can be shown with its help.

Which User Exits are available in Informatica MDM?

Match User Exit: Enhances default matching rules by personalizing match logic.

Merging User Exit: Has an impact on the merging logic, particularly in the rules governing survivorship.

Load User Exit: Adjusts or enhances data as it is being loaded.

Unmerge User Exit: When unmerging records, introduce custom logic.

Tokenization User Exit: Modifies the matching’s default tokenization procedure.

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Describe data governance and its connection to Informatica MDM.

In Informatica MDM, “data governance” refers to the comprehensive strategy for managing, enhancing, monitoring, preserving, and safeguarding data. Data governance is made easier by Informatica MDM, which guarantees that data is reliable, consistent, and not duplicated. This entails setting up procedures, roles, guidelines, and standards for the collection, use, and disposal of data.

In MDM, how do you manage real-time processing?

MDM’s Services Integration Framework (SIF) handles real-time processing. With the use of SIF’s APIs, external apps can communicate with MDM in real-time for tasks including record retrieval, insertion, updating, and deletion.

SIF: Provides instantaneous API-based MDM access.

Integration: instantaneous synchronization of data with the systems of origin.

Message Queues: For instantaneous data handling, use systems such as Kafka.

Validation: Compare and instantly verify incoming data.

How do the Informatica MDM Safe and Survivorship Rules operate?

In the event of a dispute during the merge process, the Safe and Survivorship Rules specify which source’s data is deemed more trustworthy. Which data from each record will “survive” and be included in the combined record at the end is determined by survival rules. To preserve confidence and data integrity, these guidelines are essential.

Informatica MDM Packages: What Are They?

Packages in MDM are groups of metadata definitions, such as merge and match rules, table definitions, etc. They make migration and deployment easier by being able to be exported from one environment and imported into another.

Object grouping: Combine relevant MDM objects, such as rules and mappings.

Migration: moving configurations from one environment to another (from development to production, for example).

Version Control: Monitor and oversee various package versions.

Explain the MDM data profiling process.

Examining, evaluating, and assessing data to comprehend its relationships, quality, structure, trends, and anomalies is the process known as data profiling.

This is crucial in Informatica MDM before putting data quality standards into practice since it provides information about the data’s existing condition.

Describe the Hub State Indicator’s (HSI) function.

Every entry in the MDM base object tables has a flag called the Hub State Indicator (HSI). It indicates the record’s current status, indicating if it is an original record, a unique record after merging, or a record that was rejected because of quality concerns.

Describe MDM’s function from a customer-centric perspective.

By combining information from several sources and touchpoints, a customer’s 360-degree perspective seeks to present a comprehensive and unified picture of them. By removing duplicates, harmonizing, and cleaning up client data from many systems, MDM makes it easier to have a single, reliable version of the truth. Better analytics, customer service, and tailored marketing are all aided by this all-encompassing perspective.

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What are match columns and match paths in Informatica MDM Hub?

The match rule sets include match columns and match paths. The tables (such as Base Object and Cross-Reference) from which the match key is constructed are specified by the Match Path, and the particular columns from those tables that are utilized in the match process are designated as the Match Columns.

Explain the meaning of the external match.

With an external match, Informatica MDM can make use of a matching engine or algorithm other than the built-in default.

When companies choose to use sophisticated or specialized matching solutions, or when they have certain matching criteria, this is advantageous.

How is data quality ensured by MDM?

Through many procedures like data cleansing, standardization, deduplication, and validation, MDM guarantees the quality of the data. MDM may convert unprocessed data into consistent, dependable, and usable master data by utilizing rules and workflows.

In Informatica MDM, how are relationships maintained?

The Relationship Management module of Informatica MDM is used to handle relationships. Users can define, display, and manage hierarchical structures, parent-child relationships, peer-to-peer interactions, and other complicated relationships between entities with this module.

Could you elaborate on the Informatica MDM token concept?

Smaller bits created from data attributes, mostly employed in the matching process, are referred to as tokens in Informatica MDM.

Tokenization could split the name “Jonathan Doe” into “Jonathan” and “Doe,” for example.

Tokenization aids in the decomposition of data to enable more precise and efficient matching.

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