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

Overview Organizations today rely on data-driven decision-making, but managing massive datasets across cloud platforms can be complex. DP-3011 Implementing a Data Analytics Solution with Azure Databricks equips data professionals to prepare, analyze, and govern data at scale using Apache Spark’s distributed computing capabilities. _ In this one-day training, you’ll gain hands-on experience with Delta Lake for versioning and data integrity, automate data pipelines with Delta Live Tables, and implement governance with Unity Catalog. You’ll also explore Spark for large-scale data analysis, orchestrate workflows for production deployments, and collaborate in Python and SQL notebooks to deliver high-quality analytics-ready data. Course Objectives By the end of this course, participants will have the confidence to prepare and analyze data in Azure Databricks while applying governance and automation best practices. You will learn to: _ Explore Azure Databricks workloads and core components Perform large-scale data analysis with Spark and DataFrame APIs Manage transactions, schema enforcement, and versioning with Delta Lake Build automated data pipelines using Delta Live Tables Implement governance using Unity Catalog and Microsoft Purview Deploy production workloads with Azure Databricks Workflows Who Should Attend? This course is ideal for data analysts and data professionals who work with large datasets and want to leverage Azure Databricks for advanced analysis and pipeline automation. It is especially valuable for those responsible for preparing data for downstream analytics, applying governance to data lakes, and collaborating in notebook-based environments. Course Prerequisites Familiarity with SQL and basic Python Working knowledge of Azure fundamentals Basic understanding of data engineering or analytics workflows Course Outline Explore Azure Databricks Introduction to Azure Databricks Identify common Azure Databricks workloads Review essential concepts Apply data governance with Unity Catalog and Microsoft Purview Module assessment Perform Data Analysis with Azure Databricks Ingest data into Azure Databricks Use built-in tools for data exploration Perform analysis with DataFrame APIs Module assessment Use Apache Spark in Azure Databricks Introduction to Apache Spark Configure and create a Spark cluster Work with Spark inside notebooks Process various data files with Spark Visualize data using Spark Module assessment Manage Data with Delta Lake Introduction to Delta Lake Work with ACID transactions Enforce schema rules Apply data versioning and time travel in Delta Lake Ensure data integrity with Delta Lake Module assessment Build Data Pipelines with Delta Live Tables Introduction to Delta Live Tables Manage data ingestion and integration Enable real-time data processing Module assessment Deploy Workloads with Azure Databricks Workflows Overview of Azure Databricks Workflows Understand the core components of workflows Examine the benefits of Azure Databricks Workflows Deploy workloads through Azure Databricks Workflows Module assessment