Orchestrating Big Data with Azure Data Factory
Rp500,000 Rp99,000
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Description
About this course
This course is part of the Microsoft Professional Program Certificate in Big Data.
Need to schedule and manage big data workflows?
This data analysis course teaches you how to use Azure Data Factory to coordinate data movement and transformation using technologies such as Hadoop, SQL, and Azure Data Lake Analytics. You will learn how to create data pipelines that will allow you to group activities to perform a certain task.
Note: To complete this course, you will need a Microsoft Azure subscription. You can sign up for a free trial subscription at http://azure.microsoft.com, or you can use your existing subscription. The labs have been designed to minimize the resource costs required to complete the hands-on activities.
What you’ll learn
- Creating data workflows with Azure Data Factory
- Scheduling data pipelines to orchestrate big data processes
- Applying data transformations in a pipeline with Hive or U-SQL
Estimate Time : 12-16 hours
Module 1 Introduction to Azure Data Factory
- Getting Started with Azure Data Factory
- Lab
Module 2 Pipelines
- Introduction to Pipelines
- Lab
Module 3 Scheduling Pipelines
- Overview of Pipeline Scheduling
- Lab
Module 4 Transformations
- Introduction to Transformations
- Lab
Graeme Malcolm
Senior Content Developer Microsoft Learning Experiences
Graeme has been a trainer, consultant, and author for longer than he cares to remember, specializing in SQL Server and the Microsoft data platform. He is a Microsoft Certified Solutions Expert for the SQL Server Data Platform and Business Intelligence. After years of working with Microsoft as a partner and vendor, he now works in the Microsoft Learning Experiences team as a senior content developer, where he plans and creates content for developers and data professionals who want to get the best out of Microsoft technologies.
Additional information
Author / Publisher | Microsoft |
---|---|
Level | Beginner, Intermediate |
Language | English |
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