Data Quality Management Framework
About This Course
The WSQ Data Quality Management Framework course equips participants with essential skills to drive consistency and accuracy in data analysis. Learners will explore the key dimensions of data quality, understand the impact of poor data, and identify potential threats. Participants will also gain insights into the principles of the data quality management framework and its role in achieving reliable data-driven decision-making.
This course delves into practical techniques for measuring and enhancing data quality. Participants will learn how to apply data profiling, parsing, standardisation, cleansing, and data linkage to ensure clean, usable data. By mastering data quality governance, roles, and best practices, learners will be equipped to design robust strategies for improving data quality within their organisations.
What You'll Learn
LO1: Drive consistency and accuracy in data analysis by applying data quality management framework.
LO2: Synthesise findings from multiple research studies to measure data quality to derive new insights in professional research areas.
LO3:Evaluate design strategies to maximize data quality for improved alignment with organisational, funding, or policy priorities
Topics Covered:
Topic 1: Introduction to Data Quality Management Framework
• What is data quality?
• Overview of data quality management framework
• Impact of poor data quality
• Potential threats to data quality
Topic 2 Key Dimensions of Data Quality
• The Six Dimensions of data quality - Accuracy, Completeness, Timeliness, Validity, Uniqueness, Consistency
• Identifying opportunities for synergies in data analyses across research studies across organizations,
Topic 3: Measuring Data Quality
• Data quality rules
• Data quality processes
o data profiling
o data parsing
o data standardization
o identity resolution
o data linkage
o data cleansing
o data enhancement
o data inspection and monitoring
• Metrics for measuring data quality.
• Trade-offs in data dimensions
• How good data quality support the synthesis of findings from multiple research studies?
Topics 4: Design Strategies for Maximizing Data Quality
• Data quality roles
• Data quality improvement process
• Data quality techniques and tools
• Data quality governance
• Data quality best practices.
• How data quality impact the research results in areas of interest to organization?
• Evaluate design strategies to maximize data quality for better alignment with organization priorities.
Entry Requirements
Knowledge and Skills
• Able to operate computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
• Positive Learning Attitude
• Enthusiastic Learner
Experience
• Minimum of 1 year of working experience.
Target Year Group : 21-65 years old