Learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run large data engineering workloads in the cloud.
After completing this course, students will be able to:
Provision an Azure Databricks workspace
Identify core workloads for Azure Databricks
Use Data Governance tools Unity Catalog and Microsoft Purview
Ingest data using Azure Databricks
Using the different data exploration tools in Azure Databricks
Analyse data with DataFrame APIs
Describe key elements of the Apache Spark architecture
Create and configure a Spark cluster
Describe use cases for Spark
Use Spark to process and analyse data stored in files
Use Spark to visualise data
How to manage ACID transactions using Delta Lake
How to use schema versioning and time travel in Delta Lake
How to maintain data integrity with Delta Lake
Describe Delta Live Tables
Ingest data into Delta Live Tables
Use Data Pipelines for real time data processing
The key components and benefits of Azure Databricks Workflows
How to deploy workloads using Azure Databricks Workflows
As part of Lumify Group, Lumify Work has skilled more people in Microsoft technologies than any other organisation in Australia and New Zealand. We have a campus in the Philippines, too. We offer the broadest range of instructor-led training courses, from end user to architect level. We are proud to be the winner of the Microsoft MCT Superstars Award for FY24, which formally recognises us as having the highest quality Microsoft Certified Trainers in ANZ.
Data Engineers
Fundamental knowledge of data analytics concepts
The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.
