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Mastering Databricks SQL Warehouse and Spark SQL

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A Comprehensive Course on Databricks SQL Warehouse and Spark SQL for Data Engineers, Data Analysts, BI Developers, etc

Databricks SQL Warehouse is relatively new technology to build Data Lakehouse or Data Warehouse leveraging powerful Apache Spark Engine where the analytics can be built at scale. As part of this comprehensive course, you will learn all key skills required to master Databricks SQL Warehouse including Spark SQL as the SQL in Databricks SQL Warehouse is based on Spark SQL.

What you’ll learn

  • Setup Databricks SQL Warehouse Environment using Azure Databricks for hands-on Practice.
  • Getting Started with Databricks SQL for Data Analysis or Data Engineering.
  • Features of Databricks SQL Warehouse – Clusters, Query Editor, Visualizations and Dashboards, etc.
  • Overview of building reports and dashboards using Databricks SQL.
  • Creating Databases and Tables using Databricks SQL or Spark SQL.
  • Writing Basic Queries using Databricks SQL or Spark SQL.
  • DML to load data into Databricks SQL or Spark SQL Tables.
  • Advanced Operations such as Ranking and Aggregations using Databricks SQL or Spark SQL.
  • Processing Semi-Structured Data using Databricks SQL or Spark SQL.
  • In-depth Coverage about Delta Tables including all possible DML Operations such as Insert, Update, Delete, Merge, etc.
  • End to End Life Cycle of Data Analysis of Data in Files using Databricks (Uploading File to Databricks to Reports and Dashboards).

Course Content

  • Introduction to Mastering Databricks SQL Warehouse and Spark SQL –> 1 lecture • 4min.
  • Setup Databricks Environment using Azure –> 16 lectures • 1hr 4min.
  • Setup Course Material and Environment for Databricks SQL –> 3 lectures • 12min.
  • Getting Started with Databricks SQL –> 16 lectures • 1hr 4min.
  • Managing Databases using Databricks SQL Warehouse –> 9 lectures • 35min.
  • Manage Delta Tables in Databricks SQL Warehouse –> 12 lectures • 57min.
  • Setup Data Set for Databricks SQL Views and Copy Commands –> 9 lectures • 39min.
  • Queries to Process Values in JSON String Columns –> 8 lectures • 37min.
  • Copy Data into Delta Tables in Databricks SQL Warehouse –> 9 lectures • 36min.
  • Insert or Merge Query Results or View into Delta Tables using Databricks SQL –> 11 lectures • 50min.
  • Merge Query Results and Data with Delete into Delta Tables using Databricks SQL –> 12 lectures • 56min.
  • Getting Started with Basic SQL Queries using Databricks SQL –> 17 lectures • 1hr 9min.

Mastering Databricks SQL Warehouse and Spark SQL

Requirements

Databricks SQL Warehouse is relatively new technology to build Data Lakehouse or Data Warehouse leveraging powerful Apache Spark Engine where the analytics can be built at scale. As part of this comprehensive course, you will learn all key skills required to master Databricks SQL Warehouse including Spark SQL as the SQL in Databricks SQL Warehouse is based on Spark SQL.

This course also covers most of the curriculum relevant to clear the Databricks Certified Data Analyst Associate Exam offered by Databricks itself.

Here are the high-level details related to this course. This is a beginner level course where you will be able to not only learn syntax and semantics of Databricks SQL or Spark SQL, you will also understand the concepts of the same.

  • Setup Course Material and Environment for Databricks SQL Warehouse
  • Managing Databases using Databricks SQL Warehouse
  • Manage Delta Tables in Databricks SQL Warehouse
  • Setup Data Set for Databricks SQL Views and Copy Commands
  • Databricks SQL or Spark SQL Queries to Process Values in JSON String Columns
  • Copy Data into Delta Tables in Databricks SQL Warehouse
  • Insert or Merge Spark SQL or Databricks SQL Query Results or View into Delta Tables
  • Merge Spark SQL or Databricks SQL Query Results and Data from Delta Table with Delete into Delta Tables
  • Basic SQL Queries using Spark SQL or Databricks SQL
  • Performing Aggregations using Group By and filtering using Having leveraging Spark SQL or Databricks SQL
  • Aggregations using Windowing or Analytical Functions including Cumulative Aggregations using Spark SQL or Databricks SQL
  • Ranking using Windowing or Analytical Functions using Spark SQL or Databricks SQL
  • Dealing with different file formats such as parquet, json, csv, etc using Spark SQL or Databricks SQL
  • All Important types of Joins such as Inner, left or right outer, full outer using Spark SQL or Databricks SQL
  • Visualizations and Dashboards using Databricks SQL Warehouse

We have also provided quite a few exercises along with solutions with explanations through the course.

Key Takeaways of Mastering Databricks SQL and Spark SQL using Databricks SQL Warehouse

  • Setup Environment to learn Databricks SQL and Spark SQL using Azure
  • Support via Udemy Q&A backed by our expert team
  • Data Sets and Material via GitHub Repository along with instructions to practice Databricks SQL or Spark SQL
  • Life Time Access to High Quality Video Lectures to learn Databricks SQL and Spark SQL
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