Mastering Databricks SQL Warehouse and Spark SQL
- IT & Software
- Nov 30, 2024

Mastering Databricks SQL Warehouse and Spark SQL, available at $54.99, has an average rating of 4.35, with 198 lectures, based on 315 reviews, and has 2571 subscribers.
You will learn about 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) This course is ideal for individuals who are Data Analysts and BI Developers who want to understand Databricks SQL or Spark SQL Queries to analyze the data or Data Engineers who would like to understand Databricks SQL or QA Analysts or Engineers who would like to understand Databricks SQL for the validation of the data or Business Analysts to analyze the Data in the Data Lake using Databricks SQL or Spark SQL Queries or BI Developers who want to understand how to connect BI Tools to Databricks SQL Endpoint and develop required reports and dashboards It is particularly useful for Data Analysts and BI Developers who want to understand Databricks SQL or Spark SQL Queries to analyze the data or Data Engineers who would like to understand Databricks SQL or QA Analysts or Engineers who would like to understand Databricks SQL for the validation of the data or Business Analysts to analyze the Data in the Data Lake using Databricks SQL or Spark SQL Queries or BI Developers who want to understand how to connect BI Tools to Databricks SQL Endpoint and develop required reports and dashboards.
Enroll now: Mastering Databricks SQL Warehouse and Spark SQL
Summary
Title: Mastering Databricks SQL Warehouse and Spark SQL
Price: $54.99
Average Rating: 4.35
Number of Lectures: 198
Number of Published Lectures: 198
Number of Curriculum Items: 198
Number of Published Curriculum Objects: 198
Original Price: $24.99
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
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
Course Curriculum
Chapter 1: Introduction to Mastering Databricks SQL Warehouse and Spark SQL
Lecture 1: Introduction to Mastering Databricks SQL Warehouse and Spark SQL
Chapter 2: Setup Databricks Environment using Azure
Lecture 1: Introduction to Setup Databricks Environment using Azure
Lecture 2: Signup for Azure Portal
Lecture 3: Setup Azure Databricks using Azure Portal
Lecture 4: Launching Azure Databricks Environment
Lecture 5: Create Single Node Databricks Cluster
Lecture 6: Editing Databricks Clusters using Databricks UI
Lecture 7: Getting Started with Databricks Notebooks
Lecture 8: Create Databricks SQL Warehouse
Lecture 9: Increase Quota to Create Databricks SQL Warehouse Cluster
Lecture 10: Run Queries using Databricks SQL Warehouse
Lecture 11: Overview of Uploading Data using Databricks SQL Warehouse UI
Lecture 12: Review Data Explorer of Data Science and Engineering Environment
Lecture 13: Analyze Sales Data using Databricks Notebooks
Lecture 14: Terminate Databricks Data Science and Engineering Clusters
Lecture 15: Terminate Databricks SQL Warehouse Clusters
Lecture 16: Delete Azure Databricks Workspace
Chapter 3: Setup Course Material and Environment for Databricks SQL
Lecture 1: Install Databricks CLI using Python 3 Pip Command
Lecture 2: Configure Databricks CLI using Token and Profile
Lecture 3: Setup Git Repository for Material and Data Sets related to Databricks SQL Course
Chapter 4: Getting Started with Databricks SQL
Lecture 1: Overview of Databricks SQL Platform – Introduction
Lecture 2: Run First Query using SQL Editor of Databricks SQL
Lecture 3: Overview of Dashboards using Databricks SQL
Lecture 4: Overview of Databricks SQL Data Explorer to review Metastore Database and Tables
Lecture 5: Use Databricks SQL Editor to develop scripts or queries
Lecture 6: Review Metadata of Tables using Databricks SQL Platform
Lecture 7: Overview of loading data into retail_db tables
Lecture 8: Configure Databricks CLI to push data into Databricks Platform
Lecture 9: Copy JSON Data into DBFS using Databricks CLI
Lecture 10: Analyze JSON Data using Spark APIs
Lecture 11: Analyze Delta Table Schemas using Spark APIs
Lecture 12: Load Data from Spark Data Frames into Delta Tables
Lecture 13: Run Adhoc Queries using Databricks SQL Editor to validate data
Lecture 14: Overview of External Tables using Databricks SQL
Lecture 15: Using COPY Command to Copy Data into Delta Tables
Lecture 16: Manage Databricks SQL Endpoints
Chapter 5: Managing Databases using Databricks SQL Warehouse
Lecture 1: Review Databases using Databricks SQL Data Explorer
Lecture 2: Create Database or Schema using Databricks SQL
Lecture 3: Using IF NOT EXISTS while Creating Databases using Databricks SQL
Lecture 4: Listing or Showing Databases and Getting Metadata of Databases using Databricks
Lecture 5: Understand Default Location of Databricks SQL Database or Schema
Lecture 6: Create Database or Schema using Location in Databricks SQL Warehouse
Lecture 7: Drop Databases in Databricks SQL Warehouse
Lecture 8: Alter Database in Databricks SQL Warehouse
Lecture 9: Comments on Databases in Databricks SQL Warehouse
Chapter 6: Manage Delta Tables in Databricks SQL Warehouse
Lecture 1: List Databases and Save Databricks SQL Script
Lecture 2: Create Table using Delta Format in Databricks SQL Warehouse
Lecture 3: Understand Location and Using Clause to specify File Format for Databricks
Lecture 4: Create External Table using Delta Format in Databricks SQL Warehouse
Lecture 5: Drop External Table and Delete Folder in Databricks SQL Warehouse
Lecture 6: Overview of DML or CRUD Operations using Databricks SQL
Lecture 7: Insert Records into Databricks SQL Warehouse table
Lecture 8: Insert Multiple Records into Databricks SQL Warehouse table
Lecture 9: Update Existing Records in Databricks SQL Warehouse table
Lecture 10: Update Existing Records in Databricks SQL Warehouse table based on Null Values
Lecture 11: Delete Existing Records in Databricks SQL Warehouse table
Lecture 12: Cleanup Users Tables from Databricks SQL Warehouse Database or Schema
Chapter 7: Setup Data Set for Databricks SQL Views and Copy Commands
Lecture 1: Getting Started with Databricks fs Commands using Databricks CLI
Lecture 2: Create Folder in DBFS using Databricks CLI Commands
Lecture 3: Copy Files from Local File System into DBFS using Databricks CLI Commands
Lecture 4: Overwrite Files while Copying into DBFS using Databricks CLI Command
Lecture 5: Understand Course Catalog Data in the files uploaded to DBFS
Lecture 6: Options to Analyze Data using Databricks SQL Queries
Lecture 7: Run Select Queries using DBFS Path in From Cluase
Lecture 8: Run Queries using Temporary Views in Databricks SQL
Lecture 9: Run Queries using External Tables in Databricks SQL
Chapter 8: Queries to Process Values in JSON String Columns
Lecture 1: Queries to Process Values in JSON String Columns
Lecture 2: Get Distinct and Count based on Key using Course Catalog Data
Lecture 3: Filter Data using Basic Databricks SQL Queries using Course Catalog Data
Lecture 4: Exploring Functions using Databricks SQL
Lecture 5: Understand Record Column Values in Course Catalog Table
Lecture 6: Processing JSON String Values using Databricks SQL Queries
Lecture 7: Process Instructors JSON Records using Databricks SQL Queries
Lecture 8: Create View for Instructors using Databricks SQL Queries
Chapter 9: Copy Data into Delta Tables in Databricks SQL Warehouse
Lecture 1: Create Delta Table for Course Catalog Data Set
Lecture 2: Get File Names along with Data using Databricks SQL Queries
Lecture 3: Overview of Databricks SQL COPY Command
Lecture 4: Copy Data from single file into Delta Tables using Files
Lecture 5: Copy Data from multiple files into Delta Tables using Files
Lecture 6: Copy Data from multiple files into Delta Tables using Pattern
Lecture 7: Create Course Catalog Table in Databricks SQL Warehouse with additional Column
Lecture 8: Copy Data from Files using Queries into Delta Tables
Lecture 9: Validate Course Catalog Table in Bronze Layer
Chapter 10: Insert or Merge Query Results or View into Delta Tables using Databricks SQL
Lecture 1: Introduction to Insert or Merge Query Results or View into Delta Tables using D
Lecture 2: Create Course Catalog and Instructors Tables using Databricks SQL
Lecture 3: Copy Data into Course Catalog Table from JSON Files using Databricks SQL
Lecture 4: Insert Query Results into Delta Table using Databricks SQL
Lecture 5: Exercise to Create Courses Table and Insert Data
Lecture 6: Copy Instructors Data into Course Catalog Table from new file
Lecture 7: Understand the Concept of Merge or Upsert in DML or CRUD Operations
Instructors

Durga Viswanatha Raju Gadiraju
CEO at ITVersity and CTO at Analytiqs, Inc

Pratik Kumar

Sathvika Dandu

Madhuri Gadiraju

Sai Varma

Phani Bhushan Bozzam
Rating Distribution
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