Microsoft Azure Databricks Administration - ETL Workflow

Description

In this Course, you will learn about spark based Azure Databricks, with more and more data growing daily take it any source be it in csv, text , JSON or any other format the consumption of data has been really easy via different IoT system. mobile phones internet and many other devices.

Azure Databricks provides the latest versions of Apache Spark and allows you to seamlessly integrate with open source libraries. Spin up clusters and build quickly in a fully managed Apache Spark environment with the global scale and availability of Azure.

Here is the 30,000 ft. overview of the agenda of the course, what will you learn and how you can utilise the learning into a real world data engineering scenario, this course is tailor made for some one who is coming from a background with no prior knowledge of Databricks and Azure and would like to start off their career in data world, specially around administering Azure Databricks.

Prepare for Azure Databricks Certified Associate Platform Administrator by solving practise questions.

Prepare for interviews and certification by solving quizzes at the end of sessions.

1. What is Databricks?

2. Databricks Components:

a. Notebook

b. Clusters

c. Pool

d. Secrets

e. Databricks CLI

f. Cluster Policy

3. Automate the entire administration activity via Terraform.

4. Mount Azure Blob Storage with Databricks.

5. Automate mount Azure Blob Storage with Databricks.

6. Load CSV data in Azure blob storage

7. Transform data using Scala and SQL queries.

8. Load the transform data into Azure blob storage.

9. Understand about Databricks tables and filessystem.

10. Configure Azure Databricks logging via Log4j and spark listener library via log analytics workspace.

11. Configure CI CD using Azure DevOps.

12. Git provider intergration.

13. Configure notebook deployment via Databricks Jobs.

What You Will Learn!

• Learn about Azure Databricks fundamentals, components of databricks like notebooks, cluster, pool, cluster policies,databricks cli, secret management.
• How to enable logging in databricks using Azure log analytics workspace libraries, deploy JAR and query logs using Kusto query language for your spark app.
• Integrate databricks notebook with Git providers like Github.
• Automate administration of Azure Databricks and resources via Terraform for multiple environments.
• Learn how to transform smaller datasets in csv, in Scala and SQL and push transformed data into Azure blob storage and databricks table.
• Prepare for Azure Databricks Certified Associate Platform Administrator by solving practise questions.
• Configure Continuous Integration and Delivery of your spark application using Azure DevOps, datathrust templates.
• Run notebook on Azure Databricks via Jobs.
• Manage your Databricks cluster using Databricks CLI.

Who Should Attend!

• Data Engineers
• Infrastructure Engineers
• Databricks Engineers
• DataOps

TAKE THIS COURSE