Databricks Lakehouse Fundamentals Course Overview

Databricks Lakehouse Fundamentals Course Overview

The Databricks Lakehouse Fundamentals course offers a comprehensive introduction to the powerful Lakehouse architecture. Participants will explore key concepts of data engineering and analytics, learning how to effectively manage data in a unified platform. The primary learning objectives include understanding the advantages of the Lakehouse model, mastering data ingestion and transformation techniques, and developing skills for leveraging machine learning within Databricks.

Through practical applications, learners will gain hands-on experience in building robust data pipelines and employing visualization techniques to derive actionable insights. This course equips professionals with the essential tools to drive data-driven decision-making in their organizations, making it an invaluable addition to any IT training portfolio.

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  • Live Training (Duration : 16 Hours)
  • Per Participant
  • Classroom Training fee on request

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You can request classroom training in any city on any date by Requesting More Information

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Target Audience for Databricks Lakehouse Fundamentals

Databricks Lakehouse Fundamentals is a foundational course designed for professionals seeking to leverage the Databricks Lakehouse platform for data management and analytics, enhancing their data-driven decision-making capabilities.


  • Data Analysts
  • Data Engineers
  • Data Scientists
  • Business Intelligence Analysts
  • Machine Learning Engineers
  • Database Administrators
  • IT Professionals
  • Software Developers
  • Solution Architects
  • Project Managers
  • Business Analysts
  • Digital Marketing Analysts
  • Financial Analysts
  • Research Analysts
  • Technical Consultants


Learning Objectives - What you will Learn in this Databricks Lakehouse Fundamentals?

Introduction to Course Learning Outcomes

The Databricks Lakehouse Fundamentals course equips students with essential knowledge and skills to leverage the Lakehouse architecture, covering core concepts and practical applications for data management and analysis.

Learning Objectives and Outcomes

  • Understand the architecture and components of the Databricks Lakehouse.
  • Explore Delta Lake and its role in data reliability and consistency.
  • Learn how to ingest and process data in a Lakehouse environment.
  • Utilize Databricks for data analytics and machine learning workflows.
  • Gain proficiency in SQL syntax for querying data within the Lakehouse.
  • Develop skills in data visualization and storytelling using Databricks.
  • Understand the principles of data governance within the Lakehouse framework.
  • Familiarize with integrating Databricks with popular data tools and platforms.
  • Learn best practices for optimizing performance in Databricks workloads.
  • Gain hands-on experience through practical exercises and real-world scenarios.

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