What you'll learn

Business data is usually structured for running operations, not for answering questions, which is why analysts so often face inflated totals, missing records, and the same metric reported three different ways. In this course, Data Modeling and Semantic Layers for Business Analytics, you'll gain the ability to structure and interpret analytical data models that produce reliable results.

First, you'll explore how business data is structured for analytics, including facts, dimensions, measures, the critical question of grain, and where analytical models live in a warehouse or a lakehouse. Next, you'll discover how to build, interpret, and evaluate an analytical data model, and how to diagnose the modeling faults that produce duplicated values, missing records, and misleading comparisons. Finally, you'll learn how to use a semantic layer to turn a working model into shared business meaning, with approved definitions that support consistent querying and self-serve analysis.

When you're finished with this course, you'll have the skills and knowledge to evaluate analytical data models and use semantic layers to support accurate, consistent business reporting and analysis.

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