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Case Study: Sales Analytics with Databricks Genie

BasicSkill Level
Updated 06/2026
Build a Databricks Genie space end-to-end: descriptions, synonyms, instructions, table relationships, example queries, monitoring, and benchmarks.
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DatabricksData Engineering
2 hr
4 videos
16 Exercises
1,400 XP
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Course Description

Databricks Genie answers data questions in natural language, but the quality of those answers depends on how the space is configured. In this case study, you take a Genie space through its full lifecycle. As a data analyst at Wanderbricks, you start from a minimal setup and build it out: defining column descriptions and synonyms, adding instructions, connecting tables, and saving example and parameterized queries. You then move into operations, using monitoring to surface weak answers and benchmark questions to measure quality. By the end, you can take a Genie space from setup to production-ready.

What you'll learn

  • Differentiate how column descriptions, synonyms, instructions, and entity matching influence the SQL that Genie generates.
  • Determine when to connect tables and define relationships to support queries that span multiple tables.
  • Define shared business metrics using example queries and reusable parameterized queries.
  • Detect weak responses through Genie monitoring and identify the appropriate corrective action for each.
  • Evaluate the quality of a Genie space using a benchmark suite of questions with known answers.

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Prerequisites

Introduction to Databricks Genie
1

Launching the Sales Pilot

In this chapter, you'll set up a Genie space and make it answer reliably by adding column descriptions, synonyms, default instructions, and entity matching.
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2

Department-Wide Adoption

Next, you'll expand the space across multiple tables with relationships, and lock shared formulas using SQL examples and a parameterized Trusted Asset.
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3

Enterprise Reliability

In this final chapter, learn to harden a Genie space using monitoring, targeted fixes, and a benchmark suite so its answers stay reliable at scale.
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Case Study: Sales Analytics with Databricks Genie
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FAQs

Is this course suitable for beginners?

This is an intermediate course. You should first take Introduction to Databricks Genie, or already be comfortable asking Genie questions, reading the SQL it generates, and recognizing synonyms, relationships, and example queries.

Do I need to write SQL to take this course?

No. You never write SQL in this course. Every query is provided for you to preview, paste, and validate, though the ability to read SQL helps you confirm Genie's answers.

What will I be able to do after this course?

You will be able to configure a Databricks Genie space from initial setup to production, including descriptions, synonyms, instructions, table relationships, example and parameterized queries, monitoring, and benchmark checks.

Who will benefit most from this course?

Data analysts, analytics engineers, and BI managers responsible for making Databricks Genie a reliable resource for a business team.

What dataset does the course use?

You work with the built-in samples.wanderbricks travel-booking dataset, configuring the payments, bookings, and users tables across one continuous business scenario.

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