You are here: Home > Certifications > CIMP Certification > CIMP Tracks

CIMP Tracks

To meet CIMP academic requirements in a track (see table next page), you must complete five courses from its curriculum, including the fundamentals course (F) and at least two core courses (C). For META track, one of the completed core courses must be a data modeling course (C1) and one must be a metadata management course (C2). For IMF track, you must complete the fundamentals course plus at least one course from each core area: data management (C1), data integration (C2), and information analytics (C3).

Courses (in alphabetical order) CIMP Track
IMF DQ DG MDM META DI BA SC
Analytics-based Enterprise Performance Management







Analytics Fundamentals C3




F

Artificial Intelligence Fundamentals






C
Big Data Fundamentals C3



C
C

Conceptual Data Modeling







Crafting the Business Case for Data Quality







Curating and Cataloging Data







Data Governance for Business Leaders







Data Governance Fundamentals or Data Governance for Data Stewards C1
F C



Data Integration Techniques for Designing an ODS







Data Integration Fundamentals and Best Practices C2

C
F

Data Mining Concepts & Techniques





C
C
Data Mining in R







Data Parsing, Matching & De-duplication


C



Data Profiling
C

C2


Data Quality Assessment
C

C2


Data Quality Fundamentals or Data Quality for Data Stewards C1 F




Data Quality Scorecard
C





Data Science Fundamentals






F
Data Stewardship Fundamentals or Data Stewardship Core

C




Data Understanding and Preparation for Data Science






C
Data Virtualization




C

Data Warehousing Fundamentals C2



C

Diagnostic Analytics Using Statistical Process Control







DW and BI Data Modeling



C1


Ensuring Data Quality in Data Integration




C

Framing & Planning Data Science Projects






C
Fundamentals of Business Intelligence C3




C

Fundamentals of Data Modeling and Metadata Management or
Metadata Management for Data Stewards
C1

C F


Fundamentals of Predictive Analytics C3




C

Hadoop Fundamentals







How to Deploy Data Governance: Part 1

C




How to Deploy Data Governance: Part 2

C




Information Management Fundamentals F






Introduction to NoSQL







Location Intelligence & GIS







Logical Data Modeling



C1


MDM Fundamentals: Architecture and Implementation or MDM for Data Stewards C2

F
c


Modernizing Data Governance

C





Organizing for Data Quality







Prescriptive Analytics Using Simulation Models







Putting the Science in Data Science: Fundamentals of Research Methods







Root Cause Analysis
C





Streaming Data: Concepts, Applications, & Technologies







The Data Model Scorecard







Web Analytics





C