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CIMP certification is currently offered in five tracks:

  • Information Management Foundations (IMF)
  • Data Quality (DQ)
  • Data Governance (DG)
  • Master Data Management (MDM)
  • Data Modeling & Metadata Management (META)

The table below maps our course catalog to the curricula for CIMP tracks. Each curriculum includes the fundamentals course (marked with letter 'F'), several core courses (marked with letter 'C'), and some elective courses.

To meet CIMP academic requirements in a track, you must complete five courses from its curriculum, including the fundamentals course and at least two core courses. For META track specifically, one of the completed core courses must be a data modeling course and one must be a metadata management course.

To meet CIMP Ex academic requirements in a track, you must complete eight courses, including the fundamentals course for that track, four core courses, and two elective courses (core courses also qualify as elective). The eighth course can be chosen from the entire catalog.

See CIMP Rulebook for complete CIMP and CIMP Ex requirements beyond the coursework. To enroll in the program, choose one of our many CIMP Packages.

Courses (in alphabetical order) CIMP Track
IMF DQ DG MDM META
Assessing Business Intelligence Operations          
Best Practices in Data Resource Management          
Conceptual Data Modeling          
Creating and Implementing a Data Strategy          
Data Governance for Business Leaders     C    
Data Governance Fundamentals C   F    
Data Parsing, Matching & Deduplication (coming soon)       C  
Data Profiling   C     C
Data Quality Assessment   C     C
Data Quality Fundamentals C F C    
Data Stewardship Fundamentals     C    
Data Warehousing Fundamentals C        
DW and BI Data Modeling         C
Ensuring Data Quality in Data Integration   C      
Fundamentals of Business Intelligence C        
Fundamentals of Data Modeling and Metadata Management C       F
Fundamentals of Predictive Analytics C        
Information Management Fundamentals F   C    
Logical Data Modeling         C
MDM Architecture and Implementation       C  
MDM Fundamentals and Best Practice C     F  
MDM: Selecting a Vendor       C  
Organizing for Data Quality          
Overcoming the Challenges of Global Data       C  
Root Cause Analysis   C      
Statistical Process Control          
The Data Model Scorecard