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DataCamp

Case Study: Sales Analytics with Databricks Genie

via DataCamp

Overview

Databricks Genie answers data questions in natural language, but the quality of those answers depends on how the space is configured.

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.

Syllabus

  • 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.
  • 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.
  • 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.

Taught by

Stan Konkin

Reviews

5.0 rating, based on 1 Class Central review

4.9 rating at DataCamp based on 29 ratings

Start your review of Case Study: Sales Analytics with Databricks Genie

  • Roman Abayeneh
    I found this course helpful for understanding how Databricks Genie can be applied to sales analytics. The case-study approach made the concepts practical and easier to connect to real-world data analysis tasks.

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