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The Importance of Data Quality Assessment & Control

The module describes why effective data quality assessment & control is important to an organisation. The module explains how good data quality assessment & control can benefit an organisation.

The module then goes on to discuss how the areas of data quality assessment & control are important such as data profiling, data quality rules, data quality dimensions, data quality KPIs, data quality management information, data transformations & standardisations, data quality domains, data lineage testing & data audit, data quality issue management and data management incentivisation.

Why is Data Quality Assessment & Control Important

Learning Objectives

Learn why data quality assessment & control is important.

Learn why data profiling is important.

Learn why data quality rules are important.

Learn why data quality dimensions are important.

Learn why data quality KPIs are important.

Learn why data quality management information is important.

Learn why data transformations & standardisations are important.

Learn why data quality domains are important.

Learn why data lineage testing & data audit is important.

Learn why data quality issue management is important.

Learn why data management incentivisation is important.

Who is Suitable?

No prior knowledge is required so all Data Practitioners can undertake the course.

As this is a foundations of data management module the content is especially useful poeple who are looking for a steady paced introduction to data management. The module is also very useful for managers who need to know the fundamental information and theories in order to understand data specialists work.

Videos:

  • Why would an organisation undertake data profiling?
  • How can data profiling help to identify primary keys?
  • Why do DQ rules require significant investment from business experts?
  • Why is it useful to split data quality into dimensions?
  • Why is linking data to business processes a good idea?
  • What are the challenges when transforming and standardising data?
  • What are some problems faced when testing data lineage?
  • Why are the transformations conducted within an ETL difficult for automated tools to detect?
  • Why is Data Management incentivisation so difficult to undertake?
  • Are there any alternatives to Data Management incentivisation?

Contents:

An Interactive Presentation

10 Videos

60+ Questions

10+ Interactive Questions

3 Final Practice Tests – 30 questions over 30 minutes

Final Examination – 60 questions over 30 minutes

Certification

DQRB Certificate

4 hours of learning materials to complete.

Valid for 24 months

Only £100.00 + VAT