The Enterprise Big Data Lake pdf epub mobi txt 电子书下载 2025

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Alex Gorelik is CTO and founder of Waterline Data and the founder of three startups. He also served as GM of Informatica’s Data Quality Business Unit and managed the company’s platform and data integration technology. Also for Informatica, Alex managed a team of 400 engineers and product managers as SVP of R&D for Core Technology, developing Informatica’s platform and Data Integration technology. Alex was an IBM Distinguished Engineer and co-founder, CTO and VP of engineering at Exeros and Acta Technology. Previously, Alex was co-founder, CTO and VP of Engineering at Acta Technology (acquired by Business Objects and now marketed as SAP Business Objects Data Services). Prior to founding Acta, Alex managed development of Replication Server at Sybase and worked on Sybase’s strategy for enterprise application integration (EAI). Earlier, he developed the database kernel for Amdahl’s Design Automation group. Alex holds a B.S. in Computer Science from Columbia University School of Engineering and a M.S. in Computer Science from Stanford University.

出版者:O′Reilly

作者:Alex Gorelik

出品人:

页数:200

译者:

出版时间:2017-8-31

价格:GBP 31.99

装帧:Paperback

isbn号码:9781491931554

丛书系列:

图书标签:

计算机
Data
大数据
bigdata
Hadoop

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The data lake is a daring new approach for harnessing the power of big data technology and providing convenient self-service capabilities. But is it right for your company? This book is based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises. You’ll learn what a data lake is, why enterprises need one, and how to build one successfully with the best practices in this book.

Alex Gorelik, CTO and founder of Waterline Data, explains why old systems and processes can no longer support data needs in the enterprise. Then, in a collection of essays about data lake implementation, you’ll examine data lake initiatives, analytic projects, experiences, and best practices from data experts working in various industries.

Get a succinct introduction to data warehousing, big data, and data science

Learn various paths enterprises take to build a data lake

Explore how to build a self-service model and best practices for providing analysts access to the data

Use different methods for architecting your data lake

Discover ways to implement a data lake from experts in different industries

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读后感

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这本书很一般，讲的实践、案例太少了，不推荐阅读但因为数据湖国内讲得很少（但实践非常多），因此简单写一下我的认识一、什么是数据湖？用架构图能很快说明白，用阿里的数据架构图来说 - ODS（operational data store, staging area）存储来自各业务系统（生产系统）的原始...

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用户评价

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讲的实践、案例太少了，也很少说data warehouse怎么做，后面部分也跑偏了. 但核心还是不错的 —— data science和互联网公司的出现，产生了data lake的管理方式. 因为大家能够、也更倾向自己分析，而不是去找技术团队出数; 而且machine learning用到的数据是传统data warehouse维度建模无法给到的。self-service, 是data lake 真正的核心，而不再局限于的加工好数据出BI报表。算是解答了我为什么对data warehouse完全看不懂的原因，因为我一直用的都是data lake。很好奇国外大公司的实践到底是怎样的...

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