3 Module Data Quality Online Training
Offered through DATAVERSITY Training Center
The Data Quality Learning Plan is a collection of three courses to build fundamental knowledge of a Data Quality Program. If all three courses are completed, a certificate of completion will be issued.
Each Course Contains:
- A 55-80 minute educational training video
- Trainer: Danette McGilvray
- A 24 - 28 question exam
- Materials for each course will be made available to download once the exam has been completed
Click here to learn more about the 3 Module Data Quality Learning Plan.
Module 1: DQ1 Data Quality Essentials: What Everyone in Your Organization Needs to Know
Click here to learn more about Module 1.
It is important to understand:
- Data is a vital asset to be managed
- Data should be managed as intentionally as other assets in your organization
- Basics about data quality that anyone in an organization should know
You will learn:
- Definition of data and information quality
- Importance of data quality to your organization
- What impacts the quality of data
- Who is responsible for the quality of the data and the roles they play
- What you can do about data quality
Module 2: DQ2 Data Quality Components: Getting Started with Data Quality
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It is important to understand:
- There are many pieces and parts to be managed to ensure high quality data
- Both concepts and processes are necessary to be most effective in your data quality work
You will learn:
- The Information Environment and its impact on data quality
- The Framework for Information Quality - elements necessary for high quality data
- The Ten Steps™ Process – practical, actionable guide to create, assess, and improve the quality of your data
Module 3: DQ 3 Data Quality in Action: Putting Data Quality Into Practice
Click here to learn more about this Module 3.
It is important to understand:
- Activities impacting data quality take place throughout the organization and must be addressed in order to manage data quality well
- How data quality is put into practice
You will learn:
- Data Quality in Action Triangle – how DQ is incorporated into and carried out through programs, projects, and operational processes
- Challenges and best practices as you implement and sustain your data quality work