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

DP-3011 is about building data analytics solutions using Azure Databricks and Apache Spark. You'll learn how to ingest and transform data, manage clusters, and process large datasets. The course also covers how Databricks fits with other Azure services, so you're not learning it in isolation.

📘 Azure 👥 147 Enrolled ⏱️ 1 Day 💼 Foundation Level ⭐ 4.9 | 113 Reviews

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Course Overview

The DP-3011: Implementing a Data Analytics Solution with Azure Databricks Training goes deep on Azure Databricks, Apache Spark, and Delta Lake. You'll provision workspaces, configure SQL Warehouses, and run notebooks inside Azure Data Factory. The focus is practical. You'll spend your time setting up real analytics workflows and understanding how the pieces connect, which is what matters when you're working with data at this level.

Mode of Training

🏫 Classroom 💻 Live Online 🧪 Blended 👨‍👩‍👧‍👦 Private Group

Upcoming Schedules

Start Date Time Duration Mode Price
Apr 13, 2026 9:00 am - 5:00 pm 1 Day online
$599
Apr 27, 2026 9:00 am - 5:00 pm 1 Day online
$599
May 11, 2026 9:00 am - 5:00 pm 1 Day online
$599
May 26, 2026 9:00 am - 5:00 pm 1 Day online
$599
Jun 08, 2026 9:00 am - 5:00 pm 1 Day online
$599
+ View more schedules

What you will learn

  • Introduction to Azure Databricks
  • Setting Up Azure Databricks Workspaces
  • Data Ingestion and Processing
  • Developing Data Pipelines
  • Data Exploration and Analysis
  • Machine Learning and AI Integration
  • Optimizing and Tuning Performance
  • Security and Compliance

Who Should Attend This Course?

  • Data Engineer
  • Data Scientist

Prerequisites

  • Basic Python skills (simple scripts, common data structures)
  • Basic SQL skills (filtering, joining, aggregating data)
  • Understanding of common data file formats: CSV, JSON, Parquet
  • Familiarity with Azure Portal
  • Basic knowledge of Azure Storage

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

Explore Azure Databricks

  • Provision an Azure Databricks workspace
  • Identify core workloads for Azure Databricks
  • Use Data Governance tools Unity Catalog and Microsoft Purview
  • Describe key concepts of an Azure Databricks solution

Perform data analysis with Azure Databricks

  • Ingest data using Azure Databricks.
  • Using the different data exploration tools in Azure Databricks.
  • Analyze data with DataFrame APIs.

Use Apache Spark in Azure Databricks

  • Describe key elements of the Apache Spark architecture.
  • Create and configure a Spark cluster.
  • Describe use cases for Spark.
  • Use Spark to process and analyze data stored in files.
  • Use Spark to visualize data.

Manage data with Delta Lake

  • What Delta Lake is
  • How to create Delta Tables
  • How to use schema versioning and time travel in Delta Lake
  • How to maintain data integrity with Delta Lake

Build Lakeflow Declarative Pipelines

  • Describe Lakeflow Declarative Pipelines
  • Ingest data into Lakeflow Declarative Pipelines
  • Use Lakeflow Declarative Pipelines for real time data processing

Deploy workloads with Lakeflow Jobs

  • What Lakeflow Jobs are
  • The key components and benefits of Lakeflow Jobs
  • How to deploy workloads using Lakeflow Jobs

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