Implement a data lakehouse analytics solution w/ Azure Databricks – Intensive Training («DP311»)

1 Explore Azure Databricks
Azure Databricks is a cloud service that provides a scalable platform for data analytics using Apache Spark.

2 Perform data analysis with Azure Databricks
Learn how to perform data analysis using Azure Databricks. Explore various data ingestion methods and how to integrate data from sources like Azure Data Lake and Azure SQL Database. This module guides you through using collaborative notebooks to perform exploratory data analysis (EDA), so you can visualize, manipulate, and examine data to uncover patterns, anomalies, and correlations.

3 Use Apache Spark in Azure Databricks
Azure Databricks is built on Apache Spark and enables data engineers and analysts to run Spark jobs to transform, analyze and visualize data at scale.

4 Manage data with Delta Lake
Delta Lake is a data management solution in Azure Databricks providing features including ACID transactions, schema enforcement, and time travel ensuring data consistency, integrity, and versioning capabilities.

5 Build data pipelines with Delta Live Tables
Building data pipelines with Delta Live Tables enables real-time, scalable, and reliable data processing using Delta Lake's advanced features in Azure Databricks

6 Deploy workloads with Azure Databricks Workflows
Deploying workloads with Azure Databricks Workflows involves orchestrating and automating complex data processing pipelines, machine learning workflows, and analytics tasks. In this module, you learn how to deploy workloads with Databricks Workflows.

This course is aimed for Data Engineers, Data Analysts or Data Scientists who are Interested in learning how to use Azure Databricks for data lakehouse analytics.

• Students should have fundamental knowledge of data analytics concepts
• Students should consider completing the Azure Data Fundamentals course before starting this course