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You can't manage information effectively without understanding the data meaning, constraints and relationships. Metadata management and data modeling disciplines provide the essential tools to collect, record, and organize such knowledge. Understanding these disciplines is essential to the success of data stewards. This online training course is designed to provide foundation knowledge about the most commonly used metadata management, data modeling, and data profiling techniques.
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You will learn:
- the core elements of describing data: meaning, constraints, and relationships
- common metadata purposes: classification, description, guidance, and control
- common metadata processes, practices, and standards
- the basics of entity-relationship and dimensional data modeling
- fundamentals of data profiling
This course is geared towards:
- data stewards
- business or IT professionals who want to become data stewards
- business or IT counterparts working with data stewards
- information management professionals who want to learn about data modeling and metadata management
Module 0. About the Course (9 min)
Module 1. Metadata Basics (39 min)
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Metadata Defined
- Metadata Purpose: Classify
- Metadata Purpose: Describe
- Metadata Purpose: Guide
- Metadata Purpose: Control
- Metadata Classification
- Metadata Kinds
- Metadata Management Processes
- Metadata and IT Projects
- Metadata and Data Governance
- Metadata and Data Stewardship
- Module Summary
Module 2. Data Names, Definitions, and Structures (26 min)
- Bad Habits
- Good Practices
- Data Names
- Data Definitions
- Data Structures
- Review
Module 3. Data Modeling (24 min)
- Data Modeling Defined
- Data Modeling Purpose
- Data Modeling Purpose and Big Data
- Data Modeling and People
- Kinds of Data Models
- New Kinds of Data Models
- Data Modeling Processes
- New Process for Big Dat
- The “Things” in Data Models
- Entity-Relationship Modeling
- Dimensional Data Modeling
Module 4. Data Profiling and Data Quality Scorecard (58 min)
- What is Data Profiling
- Myth and Reality of Data Profiling
- Data Profiling Techniques
- Profiling Challenges
- Role of Profiling
- Data Profiling for Big Data
- People and Technology
- Building Data Quality Scorecard
- Module Summary
Module 5. Data Curation and Cataloging (30 min)
- Data Curation
- Why Data Curation?
- Data Cataloging
- Why Data Cataloging?
- Metadata and the Catalog
Module 6. Data Lineage and Data Sensitivity (43 min)
- Data Provenance and Data Lineage
- Data Sensitivity and Data Protection
- Module Summary
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Click here to download a more detailed outline of this course.
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This exam tests knowledge and understanding of core concepts, principles, and terminology of data modeling and metadata management.
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You will be tested in these areas:
- Basic concepts and principles of metadata management
- Basic concepts and principles of data modeling
- General data modeling terminology
- Basic steps in entity-relationship data modeling
- Basic concepts and techniques in dimensional modeling
- Foundations of subject area modeling and state-transition modeling
- Best practices in data naming and data definitions
- Basic concepts, techniques, and challenges in data profiling
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Additional Information
Number of Questions: 23
Time Limit: 40 Minutes
Passing Score: 70%
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Once you pass the exam, you will receive a Certificate of Education
documenting that you have demonstrated mastery of the topic. Course
exams count towards eLC certification programs. Visit our Certification page for more information about our various programs.
We recommend that you take detailed notes and review the course material multiple times before taking this exam. Click here to learn more about exams.
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Course Review 
