Implementing a Lakehouse with Microsoft Fabric (DP-601T00)

 

Course Overview

This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric.

Course Content

  • Introduction to end-to-end analytics using Microsoft Fabric
  • Get started with lakehouses in Microsoft Fabric
  • Use Apache Spark in Microsoft Fabric
  • Work with Delta Lake tables in Microsoft Fabric
  • Ingest Data with Dataflows Gen2 in Microsoft Fabric
  • Use Data Factory pipelines in Microsoft Fabric

Who should attend

The primary audience for this course is data professionals who are familiar with data modeling, extraction, and analytics. It is designed for professionals who are interested in gaining knowledge about Lakehouse architecture, the Microsoft Fabric platform, and how to enable end-to-end analytics using these technologies.

Prerequisites

You should be familiar with basic data concepts and terminology.

Prices & Delivery methods

Online Training

Duration
1 day

Price
  • Online Training: CAD 675
  • Online Training: US $ 675
Classroom Training

Duration
1 day

Price
  • Canada: CAD 675

Click on town name or "Online Training" to book Schedule

This is an Instructor-Led Classroom course
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This is a FLEX course, which is delivered both virtually and in the classroom.

United States

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Canada

Online Training 09:00 Central Standard Time (CST) Enroll
Online Training 09:00 Pacific Daylight Time (PDT) Enroll
Online Training 09:00 Eastern Daylight Time (EDT) Enroll
Online Training 09:00 Central Daylight Time (CDT) Enroll
Online Training 09:00 Pacific Standard Time (PST) Enroll