Overview
- Covers the life cycle of data, from building pipelines to data analytics and visualizations
- Provides use cases for real-time and batch mode processing
- Shows you how to infuse machine learning into real-time and batch mode data analytics pipelines
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Table of contents (9 chapters)
Keywords
About this book
Get a 360-degree view of how the journey of data analytics solutions has evolved from monolithic data stores and enterprise data warehouses to data lakes and modern data warehouses. You will
This book includes comprehensive coverage of how:
- To architect data lake analytics solutions by choosing suitable technologies available on Microsoft Azure
- The advent of microservices applications covering ecommerce or modern solutions built on IoT and how real-time streaming data has completely disrupted this ecosystem
- These data analytics solutions have been transformed from solely understanding the trends from historical data to building predictions by infusing machine learning technologies into the solutions
Data platform professionals who have been working on relational data stores, non-relational data stores, and big data technologies will find the content in this book useful. The book also can help you start your journey into the data engineer world as it provides an overview of advanced data analytics and touches on data science concepts and various artificial intelligence and machine learning technologies available on Microsoft Azure.
What Will You Learn
You will understand the:
- Concepts of data lake analytics, the modern data warehouse, and advanced data analytics
- Architecture patterns of the modern data warehouse and advanced data analytics solutions
- Phases—such as Data Ingestion, Store, Prep and Train, and Model and Serve—of data analytics solutions and technology choices available on Azure under each phase
- In-depth coverage of real-time and batch mode data analytics solutions architecture
- Various managed services available on Azure such as Synapse analytics, event hubs, Stream analytics, CosmosDB, and managed Hadoop services such as Databricks and HDInsight
Who This Book Is For
Data platform professionals, database architects, engineers, and solution architects
Authors and Affiliations
About the authors
Pankaj Khattar is a seasoned Software Architect with over 14 years of experience in design and development of Big Data, Machine Learning and AI based products. He currently works with Microsoft on the Azure platform as a Sr. Cloud Solution Architect for Data & AI technologies. He also possesses extensive industry experience in the field of building scalable multi-tier distributed applications and client/server based development.
You can connect with him on LinkedIn at https://www.linkedin.com/in/pankaj-khattar/
Bibliographic Information
Book Title: Data Lake Analytics on Microsoft Azure
Book Subtitle: A Practitioner's Guide to Big Data Engineering
Authors: Harsh Chawla, Pankaj Khattar
DOI: https://doi.org/10.1007/978-1-4842-6252-8
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Harsh Chawla and Pankaj Khattar 2020
Softcover ISBN: 978-1-4842-6251-1Published: 09 October 2020
eBook ISBN: 978-1-4842-6252-8Published: 08 October 2020
Edition Number: 1
Number of Pages: XVII, 222
Number of Illustrations: 134 b/w illustrations
Topics: Microsoft and .NET, Big Data