Data Quality Management : A Primer

Data Quality, Quality Measurement Dimensions, Quality Management Functions, Quality Scorecard, Best Practices and more

“Data Quality Management: A Primer” is your essential guide to the principles and practices of effective Data Quality Management. Designed for beginners, this course provides a comprehensive introduction to the key concepts and strategies needed to ensure high Data Quality.

What you’ll learn

• Understand fundamentals of Data Quality Management.
• Importance of Data Quality and impact on businesses.
• Real Examples : Highlighting cost of poor quality data.
• Develop skills to measure, monitor, communicate, and manage Data Quality effectively.
• Gain knowledge on data profiling, cleansing, and using a Data Quality Scorecard.
• Talk with confidence when it comes to Data Quality Management.

Course Content

• Introduction –> 3 lectures • 6min.
• Introduction to Data Management & Data Quality Management –> 6 lectures • 30min.
• Data Quality Measurement Dimensions –> 8 lectures • 43min.
• Data Quality Scorecard –> 4 lectures • 15min.
• Data Quality Management Functions –> 10 lectures • 43min.
• Data Quality Tools and Mistakes to Avoid –> 3 lectures • 13min.
• Wrap up –> 1 lecture • 1min.

Requirements

“Data Quality Management: A Primer” is your essential guide to the principles and practices of effective Data Quality Management. Designed for beginners, this course provides a comprehensive introduction to the key concepts and strategies needed to ensure high Data Quality.

In this course, we’ll explore:

• Understanding Data Quality & Measurement Dimensions: Delve into the fundamental dimensions of Data Quality such as accuracy, completeness, consistency, and timeliness. Learn how to evaluate and improve Data Quality in various contexts.
• Implementing Effective Data Quality Processes: Understand processes for data profiling, cleansing, validation, and monitoring. Learn how to establish and maintain processes that ensure data remains reliable and valuable.
• Utilizing the Data Quality Scorecard: Understand how to use a Data Quality Scorecard to provide a clear snapshot of data quality, track progress, and identify areas needing improvement. Learn the importance of Data Quality and the significant cost implications of poor data quality on organizational performance.
• Exploring the Impact of Data Quality on Business Decisions: Examine how high-quality data supports better decision-making and operational efficiency, and understand the broader impact of data quality on business success. We will also go through real examples highlighting the cost of poor data quality.
• Recognizing Common Data Quality Challenges: Identify common pitfalls and challenges in data quality management and more.