SQL is usually reserved for interacting with databases but in this video I show how you can use Databricks to run SQL queries against a CSV dataset. There are a few defaults that can make working with a CSV dataset problematic, like disabled schema infering and no headers. These are crucial when running SQL against the CSV since the defaults will treat every single value as a string. Although this video uses Azure Databricks, the same concepts should apply to any Databricks cluster.

In this video you will learn:

• Uploading a CSV dataset to Databricks
• Create a Notebook to work with the CSV dataset
• Find potential pitfalls in default options for CSV and SQL

• Azure Databricks, Pandas, and Opendatasets
• Free Azure Certification for Students
• Learn Azure Databricks fundamentals
• Try Azure for Free
• Introduction to Azure Databricks