Build Semantic Models in Databricks with UC Metric Views

In this course, you’ll learn how to empower your data consumers to get validated business insights with less burden on you and the rest of your enterprise's data and AI team. Through building a semantic layer on top of your gold layer, you'll offer decision makers and business analysts the opportunity to explore key business performance indicators in novel ways, while still maintaining efficient data operations and enterprise-vetted metrics.

Skill Level

Associate

Duration

Prerequisites

The content was developed for participants with these skills/knowledge/abilities:

• Ability to compose queries using Databricks SQL

• Understanding of Databricks data modeling concepts

Outline

1. Semantic Layer Fundamentals

• How metric views empower users
• How metric views fit into Databricks
• Design patterns for metric views

2. Define and Query Metric Views

• Model and define metric views

• Create a simple metric view

• Query and consume metric views

• Consume a metric view

• Defining and querying metric views

3. Design and Compose Metric Views

• Composability features of metric views

• Using window measures to meet business needs

• Windowed measures

• Build metric views

4. Metric Views in Production

• Testing, validating, and certifying metric views
• Managing the performance of metric views

• Bringing metric views to data consumers

• Additional Features Overview

5. Summary and Next Steps

• Review

• Summative lab

• Knowledge check

• Next steps

Upcoming Public Classes

Date	Time	Language	Price
Date	Time	Language	Price	Feb 23	01 PM - 05 PM (Europe/Paris)	English	$750.00

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Upcoming Public Classes

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