Implementing a Data Analytics Solution with Azure Databricks (DP-3011)

Course 8685

  • Duration: 1 day
  • Language: English
  • Level: Intermediate

Unlock the potential of Azure Databricks with our intermediate-level course designed for data professionals, including Data Engineers and Data Scientists. Dive into the realm of Apache Spark and master the utilization of powerful clusters on the Azure Databricks platform to tackle large-scale data engineering tasks in the cloud. Whether you're optimizing data pipelines, building machine learning models, or analyzing vast datasets, this course equips you with the skills and insights needed to excel in today's data-driven world.

Implementing a Data Analytics Solution with Azure Databricks (DP-3011) Delivery Methods

  • In-Person

  • Online

  • Upskill your whole team by bringing Private Team Training to your facility.

Implementing a Data Analytics Solution with Azure Databricks (DP-3011) Training Information

In this course, you will:

  • Gain hands-on experience in harnessing many of the capabilities of Azure Databricks for data engineering tasks. 
  • Enhance your proficiency in Apache Spark, a leading big data processing framework, and leverage it effectively in the cloud environment. 
  • Learn best practices for optimizing data workflows and pipelines, ensuring efficiency and scalability. 
  • Acquire the skills to build and deploy advanced machine learning models using Azure Databricks, empowering you to extract actionable insights from your data. 

Training Prerequisites

None.

Certification Information

Helps prepare for Exam DP-203: Data Engineering on Microsoft Azure 

Implementing a Data Analytics Solution with Azure Databricks (DP-3011) Training Outline

  • Get started with Azure Databricks
  • Identify Azure Databricks workloads
  • Understand key concepts
  • Get to know Spark
  • Create a Spark cluster
  • Use Spark in notebooks
  • Use Spark to work with data files
  • Visualize data
  • Get Started with Delta Lake
  • Create Delta Lake tables
  • Create and query catalog tables
  • Use Delta Lake for streaming data
  • Get started with SQL Warehouses
  • Create databases and tables
  • Create queries and dashboards
  • Understand Azure Databricks notebooks and pipelines
  • Create a linked service for Azure Databricks
  • Use a Notebook activity in a pipeline
  • Use parameters in a notebook

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Implementing a Data Analytics Solution with Azure Databricks (DP-3011) FAQs

No prior experience is required. This course is suitable for both data engineering and data science professionals looking to enhance their skills with Azure Databricks.

Absolutely! Through hands-on exercises and projects, you'll gain practical experience in harnessing Azure Databricks for various data engineering tasks, including optimizing data pipelines and building machine learning models.

This course not only covers key concepts and functionalities of Azure Databricks but also emphasizes best practices for optimizing data workflows and pipelines, ensuring you're equipped to handle real-world data challenges efficiently and effectively. 

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