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Since data quality is one of the core responsibilities of data stewards, each steward needs a foundation of concepts, principles, terminology, and methodology of data quality management. This online training course provides an overview of the field of data quality with the goal of building strong fundamental knowledge for data stewards. It covers topics ranging from data quality definitions and dimensions to key data quality management practices and methodologies as well as core data quality processes and projects.
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You will learn:
- basic concepts, principles, and practices of quality management
- how quality management principles are applied to data
- dimensions of data quality
- common causes of data quality problems
- introduction to data quality assessment
- introduction to root cause analysis
- introduction to data quality monitoring
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 quality
Module 0. About the Course (9 min)
Module 1. Data Quality Basics (64 min)
- Quality Defined
- Data Quality Defined
- Common Causes of Data Quality Problems
- Dimensions of Data Quality
Module 2. Data Quality Management (40 min)
- Data Quality Projects
- Building-In Data Quality
- Data Quality and Big Data
- Data Quality Programs
- Data Quality Profession
Module 3. Introduction to Data Quality Assessment (48 min)
- Why Assess Data Quality?
- Business Value of Data Quality
- Data Quality Assessment Approaches
- Project Team
- Project Steps
- Data Quality Rules Overview
- Recurrent Data Quality Assessment
Module 4. Data Quality Scorecard (46 min)
- What is a Data Quality Scorecard
- DQ Scorecard Case Study #1
- DQ Scorecard Case Study #2
- Typical DQ Scorecard Components
Module 5. Root Cause Analysis (53 min)
- The Nature of Cause and Effect
- Cause and Effect Misconceptions
- The Purpose of RCA
- The Process of RCA
- A First Look at Cause-Effect Models
- Verifying Cause and Effect Conclusions
- Practical Application
Module 6. Ensuring Data Quality in Data Integration (41 min)
- Data Integration Basics
- Data Quality Perspective
- Data Propagation Overview
- Real-Time Interfaces
- Batch Interfaces
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, as well as key processes and projects of data quality management.
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You will be tested in these areas:
- Quality management basics
- Data quality concepts and principles
- Data quality dimensions
- Data quality processes and projects
- Causes of data quality problems
- Basic principles of data quality assessment
- Basic principles of root cause analysis
- Basic principles of data quality monitoring
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Additional Information
Number of Questions: 25
Time Limit: 50 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 
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Course Review