DP-3011: Implementing a Data Analytics Solution with Azure Databricks

• Set up a development environment in Azure Machine Learning
• Prepare data for model training
• Create and configure a model training script as a command job
• Managing artifacts using MLflow
• Implement a model for real-time consumption

Module 1: Explore Azure Databricks

• Introduction to Azure Databricks
• Identifying Azure Databricks Workloads
• Description of key concepts
• Data governance using Unity Catalog and Microsoft Purview
• Exercise: Explore Azure Databricks

Module 2: Analyze data with Azure Databricks

• Introduction
• Data ingestion with Azure Databricks
• Data exploration tools in Azure Databricks
• Data Analysis Using DataFrame APIs
• Exercise: Exploring Data with Azure Databricks

Module 3: Using Apache Spark on Azure Databricks

• Introduction
• Discover Spark
• Creating a Spark Cluster
• Using Spark in Notebooks
• Using Spark to work with data files
• Data visualization
• Exercise: Using Spark in Azure Databricks
  

Module 4: Data Management with Delta Lake

• Introduction
• Getting Started with Delta Lake
• ACID Transaction Management
• Implementation of scheme compliance
• Data versioning and time travel in Delta Lake
• Data Integrity with Delta Lake
• Exercise: Using Delta Lake in Azure Databricks

Module 5: Building Data Pipelines with Delta Live Tables

• Introduction
• Exploring Delta Live Tables
• Data ingestion and integration
• Real-time processing
• Exercise: Creating a Data Pipeline with Delta Live Tables

Module 6: Deploying Workloads with Azure Databricks Workflows

• Introduction
• What are Azure Databricks workflows?
• Understanding the key components of Azure Databricks workflows
• Exploring the benefits of Azure Databricks workflows
• Deploying workloads using Azure Databricks workflows
• Exercise: Creating an Azure Databricks Workflow

It has no prerequisites

• Course: English / Spanish
• Labs: English / Spanish