DQ0: Data Quality Learning Plan
In the Data Quality Learning Plan, instructor Danette McGilvray examines how to better leverage a multitude of Data Quality principles and practices so that an organization can ensure they have high-quality data assets. This series of three courses helps to build a fundamental understanding of the many components involved in a Data Quality program. It discusses information quality definitions, the impact of Data Quality, roles and responsibilities, frameworks, a practical 10-step process, data assessments, best practices, challenges, implementation, and so much more. If all three courses are completed, a certificate of completion will be issued.
Learning Plan Price: $269
Individual Course Price: $99
Learning Plan CEUs: 3.5 hours
Each Course Includes:
- A 55- to 80-minute educational training video
- A 24- to 28-question exam
- Materials made available for download once the exam has been completed
- Self-paced and on-demand e-learning
- Unlimited course access
Courses within the Data Quality Learning Plan:
- Data Quality Essentials: What Everyone in Your Organization Needs to Know
- Data Quality Components: Getting Started with Data Quality
- Data Quality in Action: Putting Data Quality into Practice
We offer several bulk licensing options for corporate and group use.
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Data Quality Learning Plan
DQ1: Data Quality Essentials: What Everyone in Your Organization Needs to Know
- Why Should I Care About Data Quality?
- Feeling the Effects of Poor Quality Information
- Costs of Bad Data
- Impacts
- Raise Awareness
- What is Data Quality?
- Definitions
- Data vs. Information
- DQ Dimensions
- Interpreting Needs
- Dimensions Illustrated
- Sample Decision Criteria
- How Does Data Go Bad?
- DQ Problems
- Interdependencies Example
- The Information Life Cycle – POSMAD
- The Information Environment
- Root Causes
- Integrating Data
- Who is Responsible for Data Quality?
- General Overview
- Data Governance and Data Quality
- What Can I Do About Data Quality?
- Education
- What Did We Cover Today?
DQ2: Data Quality Components: Getting Started with Data Quality
- Context and Background
- Ensure High Quality Data
- Tools
- Big Data
- Concepts and Action
- The Framework for Information Quality
- Business Goals, Strategy, Issues, Opportunities
- POSMAD Information Lifecycle
- Key Components
- Interaction Matrix
- Samples and Questions
- Benefits
- Location and Time
- Requirements and Constraints
- Data Specifications
- The Ten Steps™ Process
- In-Depth Discussion of the Entire Process
- What We Covered Today
DQ3: Data Quality in Action: Putting Data Quality into Practice
- Context and Background
- Domains, Descriptions, Activities
- Data Quality and Governance in Action Triangle
- Put this into Action
- Projects, Programs, and Operational Processes
- Distinctions
- Definitions
- Projects and Operational Processes
- Put Data Quality and Data Governance into Place
- SDLC and Phases
- Comparisons
- Alternative Approaches
- Rule of Tens
- Critical Components
- “Worst” Practices
- Best Practices
- The Ten Steps™ and Six Sigma
- Programs and Sustaining Data Quality
- Program Concept
- Framework
- Structures
- Data Governance Support
- Challenges and Best Practices
- Balance Needs
- Tensions
- Risks
- Wrap-up and Next Steps
- Resources
Milestone
Complete All Three Data Quality Courses
1. DQ1: Data Quality Essentials – What Everyone in Your Organization Needs to Know
required
Course
It is important to understand that data is a vital asset to be managed and should be managed as intentionally as other assets in your organization, such as people and money. This course covers the basics about Data Quality that everyone in an organization should know – no matter what position or title you hold. Other areas discussed include the definition of Data Quality, why it is important, what impacts the quality of data, who is responsible, and what you can do about Data Quality.
View Details2. DQ2: Data Quality Components – Getting Started with Data Quality
required
Course
It is important to understand that there are many elements to be managed to ensure high-quality data, because both concepts and processes are necessary to be most effective in your Data Quality work. This course covers the Information Environment and its impact on Data Quality, the Framework for Information Quality, and the Ten Steps™ Process, which is a practical, actionable guide to create, assess, and improve the quality of your data.
View Details3. DQ3: Data Quality in Action – Putting Data Quality into Practice
required
Course
It is important to understand that activities impacting Data Quality take place throughout the organization and must be addressed in order to manage Data Quality well. This course examines how Data Quality is put into practice through the example of the Data Quality and Governance in Action Triangle. It also looks at challenges and best practices to be aware of as you implement and sustain your Data Quality work.
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