The Importance of Data Understanding
The module then goes on to discuss how the areas of data understanding are important such as, data modelling, data models, data keys, data dependency analysis, data relationship discovery, business glossary, data dictionaries, data definitions, metadata management and data lineage.
Learn why data understanding is important.
Learn why data modelling is important.
Learn why data models are important.
Learn why data keys are important.
Learn why data dependency analysis is important.
Learn why data relationship discovery is important.
Learn why a business glossary is important.
Learn why a data dictionary is important.
Learn why data definitions are important.
Learn why metadata management is important.
Learn why data lineage 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.
- Why is a data model helpful for business users prior to building a new system?
- Why are CDE’s defined at the logical level?
- What is the benefit to being able to join tables?
- Why is data dependency analysis done?
- Can you give an example Where full content analysis would be most appropriate?
- What are the benefits to creating a business glossary?
- Why is it important that data elements are clearly understood and distinct from other data elements?
- Why is it important to document data type?
- What are the benefits of capturing data lineage?
- Why is ambiguity in data definitions to be avoided?
An Interactive Presentation
10+ Interactive Questions
3 Final Practice Tests – 30 questions over 30 minutes
Final Examination – 60 questions over 30 minutes