COURSE OBJECTIVE:
• Analysis on the basis of supply structured data (e.g. Data Lake)
• Analysis on the basis of demand-structured data (e.g. Star Schemas)
• Decoupling point between supply and demand data structures for flexibility (e.g. Data Vault)
TARGET AUDIENCE:
All employees within an organisation who want to become familiar with the core concepts of collecting and structuring data for analysis. This is not an expert training course, but aimed at anyone who comes into contact with data processing and analysis environments.
COURSE PREREQUISITES:
No specific prior knowledge is required.
COURSE CONTENT:
• Is data a liability or an asset?
• Identifying the most important data analysis architectures and the differences between them;
• Data modelling, what is it good for?
• Differences and similarities between star schema and Data Vault models. Which one works best in which situation?
• What is a Data Vault and what can you do with it?
• Is a Data Vault the same as a data warehouse?
• In what ways can we collect data from different sources and make this data available in an integrated way for analysis purposes. (data logistics)
• How do we translate source data to a form that is usable for analysis?
FOLLOW ON COURSES:
DATAVIS: Datavisualisatie en Dashboard design
GK2911: Datamodeling
DATALIT, Data Literacy