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Data Lake for Enterprises: Lambda Architecture for building enterprise data systems
A practical guide to implementing your enterprise data lake using Lambda Architecture as the base
Key FeaturesBuild a full-fledged data lake for your organization with popular big data technologies using the Lambda architecture as the baseDelve into the big data technologies required to meet modern day business strategiesA highly practical guide to implementing enterprise data lakes with lots of examples and real-world use-casesBook DescriptionThe term "Data Lake" has recently emerged as a prominent term in the big data industry. Data scientists can make use of it in deriving meaningful insights that can be used by businesses to redefine or transform the way they operate. Lambda architecture is also emerging as one of the very eminent patterns in the big data landscape, as it not only helps to derive useful information from historical data but also correlates real-time data to enable business to take critical decisions. This book tries to bring these two important aspects — data lake and lambda architecture—together.
This book is divided into three main sections. The first introduces you to the concept of data lakes, the importance of data lakes in enterprises, and getting you up-to-speed with the Lambda architecture. The second section delves into the principal components of building a data lake using the Lambda architecture. It introduces you to popular big data technologies such as Apache Hadoop, Spark, Sqoop, Flume, and ElasticSearch. The third section is a highly practical demonstration of putting it all together, and shows you how an enterprise data lake can be implemented, along with several real-world use-cases. It also shows you how other peripheral components can be added to the lake to make it more efficient.
By the end of this book, you will be able to choose the right big data technologies using the lambda architectural patterns to build your enterprise data lake.
What you will learnBuild an enterprise-level data lake using the relevant big data technologiesUnderstand the core of the Lambda architecture and how to apply it in an enterpriseLearn the technical details around Sqoop and its functionalitiesIntegrate Kafka with Hadoop components to acquire enterprise dataUse flume with streaming technologies for stream-based processingUnderstand stream- based processing with reference to Apache Spark StreamingIncorporate Hadoop components and know the advantages they provide for enterprise data lakesBuild fast, streaming, and high-performance applications using ElasticSearchMake your data ingestion process consistent across various data formats with configurabilityProcess your data to derive intelligence using machine learning algorithmsWho this book is forJava developers and architects who would like to implement a data lake for their enterprise will find this book useful. If you want to get hands-on experience with the Lambda Architecture and big data technologies by implementing a practical solution using these technologies, this book will also help you.
Table of ContentsIntroduction to Data Comprehensive Data Lake conceptsLambda Architecture as a Pattern for Data LakeApplied Lambda for Data LakeData Acquisition of Batch Date with Apache SqoopData Acquisition of Stream Data with Apache FlumeMessaging Layer with Apache Kafka
Key FeaturesBuild a full-fledged data lake for your organization with popular big data technologies using the Lambda architecture as the baseDelve into the big data technologies required to meet modern day business strategiesA highly practical guide to implementing enterprise data lakes with lots of examples and real-world use-casesBook DescriptionThe term "Data Lake" has recently emerged as a prominent term in the big data industry. Data scientists can make use of it in deriving meaningful insights that can be used by businesses to redefine or transform the way they operate. Lambda architecture is also emerging as one of the very eminent patterns in the big data landscape, as it not only helps to derive useful information from historical data but also correlates real-time data to enable business to take critical decisions. This book tries to bring these two important aspects — data lake and lambda architecture—together.
This book is divided into three main sections. The first introduces you to the concept of data lakes, the importance of data lakes in enterprises, and getting you up-to-speed with the Lambda architecture. The second section delves into the principal components of building a data lake using the Lambda architecture. It introduces you to popular big data technologies such as Apache Hadoop, Spark, Sqoop, Flume, and ElasticSearch. The third section is a highly practical demonstration of putting it all together, and shows you how an enterprise data lake can be implemented, along with several real-world use-cases. It also shows you how other peripheral components can be added to the lake to make it more efficient.
By the end of this book, you will be able to choose the right big data technologies using the lambda architectural patterns to build your enterprise data lake.
What you will learnBuild an enterprise-level data lake using the relevant big data technologiesUnderstand the core of the Lambda architecture and how to apply it in an enterpriseLearn the technical details around Sqoop and its functionalitiesIntegrate Kafka with Hadoop components to acquire enterprise dataUse flume with streaming technologies for stream-based processingUnderstand stream- based processing with reference to Apache Spark StreamingIncorporate Hadoop components and know the advantages they provide for enterprise data lakesBuild fast, streaming, and high-performance applications using ElasticSearchMake your data ingestion process consistent across various data formats with configurabilityProcess your data to derive intelligence using machine learning algorithmsWho this book is forJava developers and architects who would like to implement a data lake for their enterprise will find this book useful. If you want to get hands-on experience with the Lambda Architecture and big data technologies by implementing a practical solution using these technologies, this book will also help you.
Table of ContentsIntroduction to Data Comprehensive Data Lake conceptsLambda Architecture as a Pattern for Data LakeApplied Lambda for Data LakeData Acquisition of Batch Date with Apache SqoopData Acquisition of Stream Data with Apache FlumeMessaging Layer with Apache Kafka
1044 pages, Kindle Edition
Published May 31, 2017
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June 14, 2020This book was the first book that I read about big data. It is conceptual and practical. If you are reading it, It is better you use the exact version of Softwares and don't install new versions, because you going to face up many challenges. After you implement the example of the book you can install new versions on other OS like Ubuntu.
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