Intermediate

Query and Explore Data in Databricks SQL

UPPER() and LOWER() — case normalization.

This training addresses a concrete problem that every data team encounters: the data lives in the lakehouse, and the team needs answers. Before Databricks SQL, the typical workflow looked like this: export the data to CSV, open it in Excel, build formulas, and get a basic answer 30 minutes later. The next day, someone asks the same question with a different filter — and it starts again.

Databricks SQL offers a straightforward alternative: write standard SQL directly against Delta tables, get results in seconds from the lakehouse, and save these queries for the entire team to reuse.

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What's inside

8 sections
  1. 1 Table of Contents
  2. 2 Training overview
  3. 3 Understanding query execution in Databricks SQL
  4. 4 Writing SQL queries for analysis
  5. 5 Organizing data for repeatable workflows
  6. 6 Demo Database Schema
  7. 7 Complete demo query reference
  8. 8 Summary of key concepts

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