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CIMP Tracks

To meet CIMP academic requirements in a track, you must complete five courses from its curriculum, including the fundamentals course (F) and at least two core courses (C).


CIMP Courses
(in alphabetical order)
CIMP Track
Data Quality
Data
Governance
Master Data
Management
Metadata
Management
Data
Architecture
Architecture and Design for Data Interoperability


C
Crafting the Business Case for Data Quality




Curating and Cataloging Data


C
Data Architecture Fundamentals



F
Data Ethics & Responsible AI: Fundamentals




Data Governance for Business Leaders




Data Governance Fundamentals
F C

Data Integration Techniques for Designing an ODS




Data Modeling Fundamentals


C C
Data Parsing, Matching & De-duplication

C

Data Privacy and Protection Fundamentals
C C

Data Profiling C

C
Data Quality Assessment C

C
Data Quality Fundamentals F



Data Quality Scorecard C



Data Quality Specialist



Data Stewardship Fundamentals
C


Deciphering Data Architecture



C
Designing and Implementing Analytics Data Architecture



C
Diagnostic Analytics Using Statistical Process Control




DW and BI Data Modeling




Ensuring Data Quality in Data Integration




How to Deploy Data Governance:
Part 1
C


How to Deploy Data Governance:
Part 2
C


Introduction to Graph Databases




Knowledge Graph Architecture for the Enterprise




MDM Fundamentals: Architecture and Implementation

F

Metadata Management Fundamentals

C F
Modernizing Data Governance




Operational Data Architecture, Part 1: The Operational Data Landscape




Operational Data Architecture, Part 2: Architectural Data Management




Organizing for Data Quality




Root Cause Analysis C



Streaming Data: Concepts, Applications, and Technologies




The Data Model Scorecard






In addition to the CIMP courses, several courses from other certification programs count as electives for various CIMP tracks, as shown below:


Non-CIMP Courses (in alphabetical order)
CIMP Track
Data Quality
Data
Governance
Master Data
Management
Metadata
Management
Data Governance for Data Stewards



Data Quality for Data Stewards



Metadata Management for Data Stewards