Peer Results
- Differentiate between data types and how they are used
- Define primary key, surrogate key, and foreign key, and know what makes a good key
- Read and interpret an entity-relationship diagram (ERD)
- Recognize different types of joins and know when to use each
- Define grain in the context of data modeling and identify in a given scenario or data set
- Know what indexes are and differentiate between nonclustered and clustered indexes
- Define table and view and know-how each is used in SAMD
- Determine when you should use early vs. late binding
- Define data lake and data warehouse
- Differentiate between star schemas and third normal form schemas
- Know why we have SAM framework architecture (Health Catalyst’s data model)
- Categorize a piece of data in a given scenario as an event, rule, population, pre-metric, metric, or summary metric
Course Description
Effective data-governance solutions begin with a deep understanding of the data. The basic principles of data modeling are essential before diving into the tools Health Catalyst offers that assist in analysis and visualization.
3 modules | 3 CLUs
Target Learners:
Average Completion Time:
Co-development Partner(s):