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Azure Data Factory Cookbook

You're reading from Azure Data Factory Cookbook Build and manage ETL and ELT pipelines with Microsoft Azure's serverless data integration service

Product type Paperback

Published in Dec 2020

Publisher Packt

ISBN-13 9781800565296

Length 382 pages

Edition 1st Edition

Tools

Azure

Concepts

Data Streaming

Authors (4):

Dmitry Anoshin

Roman Storchak

Xenia Ireton

Dmitry Foshin

View More author details

Table of Contents (12) Chapters

Preface

1. Chapter 1: Getting Started with ADF

2. Chapter 2: Orchestration and Control Flow FREE CHAPTER

3. Chapter 3: Setting Up a Cloud Data Warehouse

4. Chapter 4: Working with Azure Data Lake

5. Chapter 5: Working with Big Data – HDInsight and Databricks

6. Chapter 6: Integration with MS SSIS

7. Chapter 7: Data Migration – Azure Data Factory and Other Cloud Services

8. Chapter 8: Working with Azure Services Integration

9. Chapter 9: Managing Deployment Processes with Azure DevOps

10. Chapter 10: Monitoring and Troubleshooting Data Pipelines

11. Other Books You May Enjoy

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Creating big data pipelines using Azure Data Lake and Azure Data Factory

Running big data pipelines is an essential feature of Azure Data Factory. They allow you to ingest and preprocess data at any scale. You can program and test any ELT/ETL processes out of the web UI. This is one of the core tasks of the data engineer in your company.

Getting ready

Let's load and preprocess the MovieLens dataset (F. Maxwell Harper and Joseph A. Konstan. 2015. The MovieLens Datasets: History and Context. ACM Transactions on Interactive Intelligent Systems (TiiS) 5, 4: 19:1–19:19. https://doi.org/10.1145/2827872). It contains ratings and free-text tagging activity from a movie recommendation service.

The MovieLens dataset exists in a few sizes, which have the same structure. The smallest one has 100,000 ratings, 600 users, and 9,000 movies. The biggest one can be as big as 1.2 billion reviews, 2.2 million users, and 855,000 items.

MovieLens is distributed as a set...

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Authors (4)

Dmitry Anoshin

Dmitry Anoshin

Dmitry Anoshin is a data-centric technologist and a recognized expert in building and implementing big data and analytics solutions. He has a successful track record when it comes to implementing business and digital intelligence projects in numerous industries, including retail, finance, marketing, and e-commerce. Dmitry possesses in-depth knowledge of digital/business intelligence, ETL, data warehousing, and big data technologies. He has extensive experience in the data integration process and is proficient in using various data warehousing methodologies. Dmitry has constantly exceeded project expectations when he has worked in the financial, machine tool, and retail industries. He has completed a number of multinational full BI/DI solution life cycle implementation projects. With expertise in data modeling, Dmitry also has a background and business experience in multiple relation databases, OLAP systems, and NoSQL databases. He is also an active speaker at data conferences and helps people to adopt cloud analytics.

See other products by Dmitry Anoshin

Storchak

Storchak

Roman Storchak is a PhD, and is a chief data officer whose main interest lies in building data-driven cultures through making analytics easy. He has led teams that have built ETL-heavy products in AdTech and retail and often uses Azure Stack, PowerBI, and Data Factory.

See other products by Storchak

Xenia Ireton

Xenia Ireton

Xenia Ireton is a Senior Software Engineer at Microsoft. She has extensive knowledge in building distributed services, data pipelines and data warehouses.

See other products by Xenia Ireton

Dmitry Foshin

Dmitry Foshin

Dmitry Foshin is a business intelligence team leader, whose main goals are delivering business insights to the management team through data engineering, analytics, and visualization. He has led and executed complex full-stack BI solutions (from ETL processes to building DWH and reporting) using Azure technologies, Data Lake, Data Factory, Data Bricks, MS Office 365, PowerBI, and Tableau. He has also successfully launched numerous data analytics projects – both on-premises and cloud – that help achieve corporate goals in international FMCG companies, banking, and manufacturing industries.

See other products by Dmitry Foshin

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