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

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Course Overview

The DP-3011 course, “Implementing a Data Analytics Solution with Azure Databricks,” is designed to provide comprehensive training on using Azure Databricks to build and manage data analytics solutions. This course covers the fundamentals of Azure Databricks, including its architecture, features, and integration with other Azure services. Participants will learn to use Azure Databricks to process large volumes of data, create and manage clusters, and develop scalable data pipelines.

The course delves into the core concepts of data analytics, such as data exploration, transformation, and visualization, utilizing Apache Spark capabilities within the Azure Databricks environment. Students will gain hands-on experience with notebooks, libraries, and workflows to develop and deploy analytics solutions effectively. Emphasis is placed on practical skills for implementing end-to-end data solutions, including data ingestion, cleansing, and analysis, tailored to meet the needs of modern data-driven organizations.

By the end of the course, participants will be equipped with the skills to leverage Azure Databricks for optimizing data processing workflows, performing complex data analysis, and integrating analytics solutions within a broader cloud ecosystem.

Schedule Dates

DP-3011: Implementing a Data Analytics Solution with Azure Data bricks
16 September 2024
DP-3011: Implementing a Data Analytics Solution with Azure Data bricks
16 December 2024
DP-3011: Implementing a Data Analytics Solution with Azure Data bricks
17 March 2025
DP-3011: Implementing a Data Analytics Solution with Azure Data bricks
17 June 2025

Course Content

  • Provision an Azure Databricks workspace
  • Identify core workloads and personas for Azure Databricks.
  • Describe key concepts of an Azure Databricks solution.

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

  • Describe core features and capabilities of Delta Lake.
  • Create and use Delta Lake tables in Azure Databricks.
  • Create Spark catalog tables for Delta Lake data.
  • Use Delta Lake tables for streaming data.

  • Create and configure SQL Warehouses in Azure Databricks.
  • Create databases and tables.
  • Create queries and dashboards.

  • Describe how Azure Databricks notebooks can be run in a pipeline.
  • Create an Azure Data Factory linked service for Azure Databricks.
  • Use a Notebook activity in a pipeline.
  • Pass parameters to a notebook.

FAQs

The DP-3011 course focuses on implementing data analytics solutions using Azure Databricks. It covers how to design, develop, and manage big data solutions and advanced analytics within the Azure environment, utilizing Azure Databricks’ capabilities for data processing and machine learning.

Participants should have a foundational understanding of data analytics and experience with data engineering concepts. Familiarity with Azure services and some experience with programming languages such as Python or Scala is recommended.

The course includes:

  • Introduction to Azure Databricks and its architecture
  • Setting up and configuring Azure Databricks environments
  • Creating and managing data pipelines
  • Performing data exploration and transformation
  • Implementing machine learning workflows using Databricks
  • Optimizing and managing Spark clusters
  • Integrating Databricks with other Azure services

Participants receive access to course materials, including slides, documentation, and lab exercises. Additional resources may include online forums and support from instructors for further assistance.

 

To enroll in the DP-3011 course, visit CounselTrain’s website or contact their support team for information on course schedules, registration, and pricing.

For additional information or specific inquiries, please contact CounselTrain’s support team or visit their website for further guidance and resources.

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