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Getting Started with Greenplum for Big Data Analytics

Getting Started with Greenplum for Big Data Analytics

          
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About the Book

Explore the software components and appliance modules available in Greenplum
Learn core Big Data architecture concepts and master data loading and processing patterns
Understand Big Data problems and the data science lifecycle

Who This Book Is For
"Getting Started with Greenplum for Big Data" Analytics is great for data scientists and data analysts with a basic knowledge of Data Warehousing and Business Intelligence platforms who are new to Big Data and who are looking to get a good grounding in how to use the Greenplum Platform. It’s assumed that you will have some experience with database design and programming as well as be familiar with analytics tools like R and Weka.

What You Will Learn

Load data from multiple data sources using the built-in ELT / ETL
Learn Parallel Processing / MPP / MapReduce techniques
Program with R and MADlib
Understand back-up and recovery implementation in Greenplum
Optimize data processing and querying using optimal distribution and partitioning strategies
Exchange data between the Greenplum Database and Hadoop
Handle high-availability requirements on Greenplum
Integrate ETL, reporting, and visualization tools

In Detail
Organizations are leveraging the use of data and analytics to gain a competitive advantage over their opposition. Therefore, organizations are quickly becoming more and more data driven. With the advent of Big Data, existing Data Warehousing and Business Intelligence solutions are becoming obsolete, and a requisite for new agile platforms consisting of all the aspects of Big Data has become inevitable. From loading/integrating data to presenting analytical visualizations and reports, the new Big Data platforms like Greenplum do it all. It is now the mindset of the user that requires a tuning to put the solutions to work.

"Getting Started with Greenplum for Big Data Analytics" is a practical, hands-on guide to learning and implementing Big Data Analytics using the Greenplum Integrated Analytics Platform. From processing structured and unstructured data to presenting the results/insights to key business stakeholders, this book explains it all.

"Getting Started with Greenplum for Big Data Analytics" discusses the key characteristics of Big Data and its impact on current Data Warehousing platforms. It will take you through the standard Data Science project lifecycle and will lay down the key requirements for an integrated analytics platform. It then explores the various software and appliance components of Greenplum and discusses the relevance of each component at every level in the Data Science lifecycle.

You will also learn Big Data architectural patterns and recap some key advanced analytics techniques in detail. The book will also take a look at programming with R and integration with Greenplum for implementing analytics. Additionally, you will explore MADlib and advanced SQL techniques in Greenplum for analytics. This book also elaborates on the physical architecture aspects of Greenplum with guidance on handling high-availability, back-up, and recovery.

About the Author

Sunila Gollapudi works as a Technology Architect for Broadridge Financial Solutions Private Limited. She has over 13 years of experience in developing, designing and architecting data-driven solutions with a focus on the banking and financial services domain for around eight years. She drives Big Data and data science practice for Broadridge. Her key roles have been Solutions Architect, Technical leader, Big Data evangelist, and Mentor. Sunila has a Master's degree in Computer Applications and her passion for mathematics enthused her into data and analytics. She worked on Java, Distributed Architecture, and was a SOA consultant and Integration Specialist before she embarked on her data journey. She is a strong follower of open source technologies and believes in the innovation that open source revolution brings. She has been a speaker at various conferences and meetups on Java and Big Data. Her current Big Data and data science specialties include Hadoop, Greenplum, R, Weka, MADlib, advanced analytics, machine learning, and data integration tools such as Pentaho and Informatica. With a unique blend of technology and domain expertise, Sunila has been instrumental in conceptualizing architectural patterns and providing reference architecture for Big Data problems in the financial services domain.


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Product Details
  • ISBN-13: 9789352130191
  • Publisher: Packt
  • Binding: Paperback
  • Language: English
  • Weight: 420 gr
  • ISBN-10: 9352130197
  • Publisher Date: 2015
  • Edition: 1
  • No of Pages: 192

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