Practical Data Quality Management

Organisations are increasingly data-driven - AI systems need to be fed with trustworthy data, but poor data continues to impact, negatively affecting AI implementations, decision-making, reporting, compliance, and business operations.

Data Quality itself is changing because AI automates the way in which profiling, error detection and cleansing are completed.

Understanding how Data Quality supports AI, and how AI is influencing the way in which Data Quality Management is implemented, is vital in all environments.

This course will provide the participants with the knowledge they need to implement Data Quality Management. The Practitioners Course is designed to help those who are (or will be) responsible for managing Data Quality.

• Data Quality Awareness – What your team must understand about the importance of Data Quality (DQ)
• Data Quality in Context – The role of Frameworks, DQ Dimensions, Data Models and Metadata in the context of DQ Management
• Data Quality Management – The theory of the Data Quality practice
• Assessment – How to approach conducting a Health Check on Data, how to profile Data, and what the profiling statistics tell us
• Requirements – The requirements of business Data Producers and Consumers, rules to which Data must conform and DQ Targets and Thresholds
• Measurement – How to measure the Data based on the Business Requirements
• Correction – How to “fix” incorrect Data in terms of missing, incorrect and duplicate Data
• Prevention – How to identify the Root Causes of Data defects and stop the issues from re-occurring
• Tools – An overview of the technology to assist you, including AI
• Conclusion – We put it all together within the context of Data Management.

We designed this course to help those who are (or will be) responsible for managing Data Quality to:

• Understand the issues affecting Data Quality and recognise and quantify the symptoms
• Develop an action plan to address those issues in a controlled and repeatable process
• Demonstrate how Data Quality Management improves the business and operational ‘bottom-line’
• Maximise the use of tools to improve and monitor Data Quality
• Provide quality data to Business Processes
• Prepare you to obtain the DAMA Data Quality Specialist Certification Exam.

This course will be of interest to Data Management Practitioners, and anyone involved in Data or Information Quality Management, such as people from areas dealing with:

• Data Governance
• Master Data Management
• Business and Systems Analysis
• Data Stewardship
• Data Analysis and Cleansing.

* A certificate of attendance will be provided on completion of the course