CIMP - Data Integration


Data Integration (DI) is an essential information management capability that provides the foundation for enterprise-wide views of consistent, connected, and trusted business information. The alternative to data integration is data disparity which leads to miscommunication, misunderstanding, confusion, uncertainty, and misinformed business decisions and actions. Data integration is important, but it is complex and challenging. The variety of reasons for data integration (data warehousing, master data management, data migration, etc.), the increasing scope of data sources (enterprise data, external data, big data, web data, etc.), and the growth in data integration techniques and technologies (ETL, ELT, federation, virtualization, etc.) all contribute to data integration complexities. From defining integration requirements to acquiring and unifying data the integration choices are abundant. Effective and sustainable data integration systems depend on skilled and educated data professionals from architects to implementers. Download the Data Integration course catalogue

Our Data Integration curriculum includes 10 online courses

Each course is accompanied by an optional Certified Information Management Professional (CIMP) exam. Click on the course links to explore course details and outlines, learn more about the exams, or watch free Sneak Peeks.

You can purchase the courses individually or enroll in one of our comprehensive Education Packages at a great discount.

Product Code

Courses (in alphabetical order)

CIMP Track

Click on the links for course details



Data Integration Fundamentals and Best Practice



Data Integration Techniques for Designing an ODS



Data Parsing, Matching & De-duplication



Data Profiling



Data Quality Assessment



Data Virtualization



Data Warehousing Fundamentals



Ensuring Data Quality in Data Integration



Fundamentals of Data Modeling & Metadata Mgmt (CDS) OR



MDM Architecture and Implementation



Metadata Management for Data Stewards (CDS)


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    Data Quality Matters Jan 15, 2019 | 08:05 am

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