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Informatica Master Data Management MDM Interview Preparation

Name: Informatica Master Data Management MDM Interview Preparation
Rating: 4.4 (17 reviews)

Comprehensive Guide to Informatica MDM Concepts, Tips and Real-World Scenarios for interview preparation

Created byMDM Specialist

Last updated 2/2025

English

English [Auto],

What you'll learn

Learn about how to prepare for MDM interview
Learn about how to present MDM experience during introduction
Interview Preparation on technical topics such tables such as Landing, Staging and Base Object
Interview Preparation on job such as Landing, Stage, Load, Match and Merge
Interview Questions about records rejections
Interview Preparation on Base Object and Associated tables
Detailed preparation on Match configuration and Merge mechanism
Interview questions about Provisioning Tool
Interview questions about Entity 360 or Customer 360 Applications
Interview Questions about Repos Tables
Interview Questions about Log Files and Job monitoring

Course content

12 sections • 60 lectures • 4h 22m total length

Introduction7:04
Explore Informatica MDM interview essentials, from interview readiness and resume framing to end-to-end data flows, MDM styles, landing, staging, and load processes, including tokenization and match and merge.
Interview Readiness8:53
Prepare for Informatica MDM interviews by researching the company, understanding the job format, and crafting star-based answers; practice with mock interviews and logistics for pre, during, and post interview phases.
How should I introduce?5:16
Here is sample -

Hello, thank you for the opportunity to introduce myself. My name is XYZ, and I bring over 20 years of experience in application analysis, design, development, integration, and maintenance across diverse domains such as manufacturing, logistics, telecommunications, insurance, pharmaceuticals, transportation, and banking for mastering customer data.

I specialize in Informatica MDM (versions 9.5 to 10.x and more recently 10.5) using Jboss, Weblogic, Web sphere as application servers. I also have experience in Informatica MDM Cloud. I have extensive experience in installation, configuration using informatica MDM Hub using Cleanse and Match Server (aka Process Server), and Services Integration Framework (SIF) APIs. My expertise includes data modeling, match and merge rules configuration, hierarchy management, IDD application, Entity 360 development using Provisioning Tool, and integrating with external systems through real-time data publishing using JMS. I have also used SIF APIs and customizing MDM hub tool using User Exits.

I have worked on the complete MDM lifecycle, including data validation, creating landing, staging, and base object tables, and automating batch processes. Additionally, I’ve developed robust applications leveraging Java, J2EE, and web services with SOA architecture. I have also implemented governance practices using Axon Data Governance.

In terms of tools and technology, I have hands-on experience with Oracle, WebLogic, WebSphere, and version control tools like RTC, SVN, and JIRA, among others. My strong understanding of design patterns and frameworks, such as MVC and N-tier architecture, has been instrumental in building scalable solutions, specially in Informatica MDM.

Beyond technical expertise, I’ve been actively involved in requirement gathering, creating high-level and low-level designs, and ensuring the delivery of the best version of truth (BVT) records to downstream systems. My collaborative approach and ability to align technical solutions with business needs make me an asset to any team.

Know Your Project3:48
Abbreviations referenced in this lecture are -
UAT - User Acceptance Testing
SOA - Service-Oriented Architecture
IPS - Informatica Professional Services
Gather Project Stats3:18
Gather project stats for Informatica MDM interviews by detailing data volume, tables configured (landing, staging, base object), runtimes for stage, load, and match-and-merge, including tokenization and incremental schedules.
Data Model Implementation3:43
Explore data model implementations in Informatica MDM, focusing on party and party role models, with examples of how roles determine attributes like address, phone, and email.
Business Use Cases for MDM Implementation2:46
Refer attached document for more Business Use Cases of Informatica Master Data Management implementation.

Types of MDM Implementations2:11
Master Data Management (MDM) implementation styles refer to different approaches for implementing an MDM solution within an organization. Each style has its own characteristics and is suitable for different organizational needs and goals. Here are the four primary MDM implementation styles:

1. Registry Style:
Key Characteristics:
Source systems remain the System of Record (SOR).
MDM platform acts as a directory or index, providing a single view of master data across various sources.
Data is not replicated or consolidated in the MDM platform.
Advantages:
Minimal disruption to existing systems.
Relatively easy and quick to implement.
Lower cost compared to other styles.
Disadvantages:
Limited control over data quality and consistency.
Less effective for complex data integration and governance scenarios.
2. Consolidation Style:
Key Characteristics:
MDM platform becomes the SOR for consolidated master data.
Data is extracted from source systems, cleansed, standardized, and consolidated in the MDM platform.
Data is not typically pushed back to source systems.
Advantages:
Improved data quality and consistency.
Enhanced data analysis and reporting capabilities.
Suitable for business intelligence and data warehousing use cases.
Disadvantages:
More complex and time-consuming to implement.
Requires significant data governance and stewardship efforts.
3. Coexistence Style:
Key Characteristics:
MDM platform becomes the SOR for master data.
Data is entered and maintained in the MDM platform.
Changes made in the MDM platform are synchronized back to source systems.
Advantages:
High level of control over data quality and consistency.
Enables real-time data synchronization across systems.
Suitable for organizations with complex data integration requirements.
Disadvantages:
More complex and disruptive to implement.
Requires significant investment in data governance and stewardship.
4. Centralized Style (Transaction Style):
Key Characteristics:
MDM platform becomes the sole SOR for master data.
All master data is created, updated, and maintained in the MDM platform.
Source systems consume data from the MDM platform.
Advantages:
Highest level of control over data quality and consistency.
Enables efficient data management and governance.
Suitable for organizations with stringent data quality requirements.
Disadvantages:
Most complex and disruptive to implement.
Requires significant investment in data governance, stewardship, and IT infrastructure.
The choice of MDM implementation style depends on various factors, including the organization's specific needs, data complexity, existing IT infrastructure, and desired level of data control and governance. It is important to carefully evaluate these factors and select the style that best aligns with the organization's goals.
Data Flow2:25
Describe the three-layer data flow in Informatica MDM—upstream, MDM layer, and downstream—from source or data warehouse to cleansing and master copy, then to downstream systems with batch or real-time integration.
MDM Batch Jobs3:08
Explore the batch jobs in Informatica MDM, including land, stage, load, tokenization, match, consolidate, and publish, and how they move data from landing to the base object table.

Infrastructure or Metadata Tables in MDM3:41
The document with metadata tables along with table and column definitions is attached in resources section. The document also contains various join conditions which will be handy for quick review purposes for interview preparation.
MDM Landing Layer implementation Patterns2:51
Landing Table convention and Tables associated3:43
Explore landing tables in Informatica MDM hub, including base object and staging tables, with delta detection using contains full data set and key system columns.

Stage process and it's importance2:16
Explore the stage process in Informatica MDM, including data cleansing and transformation, data validation with rejects handling, and populating the staging table with quality checks and basic business logic.
Exploring Stage Table Configuration3:59
Configure and map staging tables under the base object, create a staging table, set up landing-to-staging mappings, and enable delta detection and audit trail.
Important Stage Table Columns3:04
Stage and Associated Tables2:31
Discover how the stage table, PRL, raw table, and rejectable are generated during mapping creation and staging table setup, with delta detection and raw retention configurations.
Raw Retention2:29
Learn how raw retention keeps the two most recent raw data runs in the raw table and deletes older raw id jobs, enabling root cause analysis and delta detection recovery.
Delta Detection process4:53
Explore delta detection by comparing landing and PRL tables to identify changes, push updates to staging, and refresh PRL from landing data, including recovery with raw tables and row IDs.
Hard Delete Detection5:36
Cleanse Functions3:14
Record Rejections Reasons5:23
Identify rejection reasons in stage and load jobs—invalid last update dates, null PKI sources, duplicates, hub state values, and lookup failures—and distinguish them via reg table and job control table.
Record Rejection Handling2:36

Base Object Table Configuration6:17
Explore base object table configuration in Informatica MDM, including history and timeline options, advanced properties like tokenization and batch settings, and how enabling history expands tables from 12 to 17.
Primary Key Columns6:00
Data Flow from Stage to Base Object5:28
Understand data flow from landing table to staging and then to base object in Informatica MDM, using the row id system and PK source object to decide inserts and updates.
Survivorship Rules2:55
In Informatica MDM, survivorship applies per field, using four rules—trust score, source last update date, row ID object, and row id xref—to select the surviving value.
Hub State Indicator3:33
Explore substrate and hub state indicators in Informatica MDM, including soft delete with hub state indicator and delete via execute batch delete, plus values active, deleted, pending, and minus nine.
Relationship between XREF and Base Object Tables3:00
Load Job Issues and Challenges3:58
Discuss load job challenges in mdm projects, including data issues with dynamic lookup values and reference data management, performance tuning, and addressing root causes such as database connections.

Factors for tokenization3:20
Understand how tokenization generates tokens from fuzzy match keys and match rules to enable accurate, scalable matching of base object records in Informatica MDM.
Tokenization Configuration1:49
Tokenization Table - Strip Table1:38
Explore how the strip table stores tokens used to match records, including SSA key and SSA data from fuzzy match rules, with invalid and preferred key indicators guiding priority.
Tokenization Job Performance Tuning7:50
Learn how tokenization performance affects load and match in Informatica MDM, and tune cryptos table properties—complete strip ratio, strip set as delete ratio, and strip set as delete upper limit.

Match and Merge Process5:08
Tables associated with Match and Merge process2:36
Explore how the MDM match process flows through bo, dirty, strip, and match tables, using tokenization and fuzzy matching to identify duplicates.
Match and Merge Configuration11:21
explore match and merge configuration for parent and child tables, including exact versus fuzzy rules, match paths, key types, and token-based matching to prevent overmatching and optimize merges.
Match Path Scenario2:45
Difference between Search Level and Match Level3:34
Explain difference between search level and match level in Informatica MDM: search level defines scope with values like typical, narrow, exhaustive; match level defines accuracy with typical, conservative, and loose.
Addressing Hotspot Issue4:45
Identify hotspot issues in Informatica MDM using match key distribution and tokenization. Address data quality hotspots such as test records by coordinating with business users to fix or delete them.
Consolidation Indicator3:40
Explore how the consolidation indicator guides the MDM match and merge process, using values 4, 3, 2, 1 and 9 to mark stages from new to hold.
Match Rule Tuning2:44
Master match rule tuning in Informatica MDM, seven steps: discuss with business users, adjust rules, define levels, add exact columns, and refine conditions and fuzzy criteria. Iterate cycles as needed.
Match Job / Process Tuning4:51

Types of User Exits4:03
User Exits Scenarios5:44
Explore MDM user exit scenarios, including stage and load exits, post landing and post load uses, survivorship rules, and unmerge handling with persistent id, hub state, and consolidation indicators.
Sample Code4:37
Explore implementing Informatica MDM user exits using Siberian jars and a resource kit. Deploy the custom post stage, post load, post match, and post merge logic in the MDM hub.

Provisioning Tool Overview2:17
Configure business entities and views with modeling, create transformations, set up tasks and extensions, and define material sets, application editor, layout designer, and Elasticsearch in the provisioning tool.
Business Entity and Business Entity View3:53
Explore how a business entity and its view power the entity 360 UI in the MDM hub, including one-to-many and one-to-one relationships, and how to model and configure them.
Transformations5:26
Master be to view and view to be transformations in the provisioning tool, used for UI display and create/update, with cleansing functions executed sequentially.
Application Designer and Layout designer3:49
Configure a 360 entity application in the provisioning tool, create the app, set a 30-minute timeout, enable queries, and design data steward layouts with the layout designer.
Task and Triggers4:21
Explore how to enable create and update operations in entity 360 ui by configuring triggers, roles, and templates for a business entity in mdm application designer.
Elastic Search configuration4:24
External Call Configuration3:37
Understanding Entity 360 Application2:45

Requirements

Basic understanding of Master Data Management project
Basic understanding of database technologies such as Oracle, REST Web Services, Json
Basic understanding of how to use Informatica MDM Hub
Basic understanding of Provisioning Tool
Basic understanding of Entity 360 or Customer 360 application and it's functionalities
Basic understanding of Business Entity Services

Description

Are you preparing for an Informatica MDM interview and unsure of what to expect? Do you want to confidently answer questions about MDM implementation, data modeling, match & merge processes, and troubleshooting techniques? If yes, then this course is designed for you!

Informatica Master Data Management (MDM) is a crucial skill in today’s data-driven world, and employers are looking for professionals who understand MDM architecture, data flow, and real-world business use cases. This course provides a structured, step-by-step approach to mastering Informatica MDM interview questions by covering essential concepts, technical insights, and common challenges faced during MDM implementations.

What You’ll Learn:

How to Prepare for an MDM Interview – Understand what employers expect and how to present your skills effectively.
Project Experience Presentation – Learn how to explain job execution timelines, record volumes, and implementation details.
Data Model & Business Use Cases – Get clarity on MDM infrastructure, tables, and business scenarios.
MDM Style Implementation – Understand different MDM architecture styles (Registry, Consolidation, Coexistence, and Centralized).
Landing, Staging, and Load Processes – Deep dive into data ingestion, transformations, and common challenges.
Match & Merge Strategies – Master exact vs. fuzzy match configurations, hotspot identification, and data merging.
User Exits & Customizations – Learn how to extend MDM functionality using custom business rules and sample code.
Provisioning Tool & Transformations – Explore entity models, transformations, and tricky questions on cleansing functions.
Log Files & Job Monitoring – Understand logs, troubleshoot issues, and ensure smooth MDM operations.

Why This Course?

Real-world Interview Questions – Covers the most commonly asked MDM interview topics.
Practical Insights – Learn not just the theory, but also how to explain and apply concepts effectively.
Easy-to-Follow Structure – Each module is designed to build upon the previous one for better understanding.
Industry-Relevant Knowledge – Stay ahead with the latest MDM trends and best practices.

By the end of this course, you’ll be fully prepared to confidently answer Informatica MDM interview questions and land your next job with ease!

Who this course is for:

Anyone who would like to excel their career as Informatica MDM Architect, Developer or Tester
Anyone who would like to become expert in MDM technologies

Informatica Master Data Management MDM Interview Preparation

What you'll learn

Explore related topics

Course content

Getting ready for MDM Interview3 lectures • 21min

Understanding Project details4 lectures • 14min

Interview Questions - Data Flow3 lectures • 8min

Interview Questions - Landing Layer3 lectures • 10min

Interview Questions - Staging Layer10 lectures • 36min

Interview Questions - Base Object Layer7 lectures • 31min

Interview Questions - Tokenization4 lectures • 15min

Interview Questions - Match and Merge process9 lectures • 41min

Interview Questions - User Exits3 lectures • 14min

Interview Questions - Provisioning Tool8 lectures • 31min

Requirements

Description

Who this course is for: