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In this course, you will explore the Databricks Data Intelligence Platform from the perspective of platform architecture, specifically related to the platform foundation in lakehouse architecture. You will learn about the scope, vision, and capabilities of a platform founded in lakehouse architecture, with a focus on how Databricks integrates with a cloud platform’s architecture. You’ll learn about the key features of a successful lakehouse implementation, specifically how to adhere to the well-architected lakehouse framework, which emphasizes structural excellence through specific dimensions, principles and best practices. You’ll also learn about data architecture strategy for the acceleration of data and AI endeavors. 

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What You'll Learn

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Who Should Attend

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Prerequisites

The content was developed for participants with these skills/knowledge/abilities:  

  • A basic understanding of data engineering principles and topics such as data collection, extraction, ingestion, and transformation.
  • Prior experience in data platform solutions architecture or similar areas of study.

Learning Journey

Coming Soon...

Databricks Overview

  • Databricks Infrastructure
  • Databricks Data Intelligence Platform
  • Unity Catalog Overview
  • Databricks Workspace Walkthrough

Exploring Lakehouse Architecture

  • The Scope of Lakehouse Architecture
  • The Modern Data and AI Platform
  • Exploring the Guiding Principles of the Lakehouse

Building a Well-Architected Lakehouse

  • Integrating Databricks with Cloud Provider Environments
  • A Well-Architected Lakehouse Framework
  • Data Architecture Strategies

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Frequently Asked Questions (FAQs)

None

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Course Curriculum

Course Curriculum

Training Schedule

Training Schedule

Exam & Certification

Exam & Certification

FAQs

Frequently Asked Questions

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