Foreword
In the last decade, we have seen the impact of exponential advances in technology on the way we work, shop, communicate, and think. At the heart of this change is our ability to collect and gain insights into data; and comments like "Data is the new oil" or "we have a Data Revolution" only amplifies the importance of data in our lives.
Tim Berners-Lee, inventor of the World Wide Web said, "Data is a precious thing and will last longer than the systems themselves." IBM recently stated that people create a staggering 2.5 quintillion bytes of data every day (that's roughly equivalent to over half a billion HD movie downloads). This information is generated from a huge variety of sources including social media posts, digital pictures, videos, retail transactions, and even the GPS tracking functions of mobile phones.
This data explosion has led to the term "Big Data" moving from an Industry buzz word to practically a household term very rapidly. Harnessing "Big Data" to extract insights is not an easy task; the potential rewards for finding these patterns are huge, but it will require technologists and data scientists to work together to solve these problems.
The book written by Sunila Gollapudi , Getting Started with Greenplum for Big Data Analytics , has been carefully crafted to address the needs of both the technologists and data scientists.
Sunila starts with providing excellent background to the Big Data problem and why new thinking and skills are required. Along with a dive deep into advanced analytic techniques, she brings out the difference in thinking between the "new" Big Data science and the traditional "Business Intelligence", this is especially useful to help understand and bridge the skill gap.
She moves on to discuss the computing side of the equation-handling scale, complexity of data sets, and rapid response times. The key here is to eliminate the "noise" in data early in the data science life cycle. Here, she talks about how to use one of the industry's leading product platforms like Greenplum to build Big Data solutions with an explanation on the need for a unified platform that can bring essential software components (commercial/open source) together backed by a hardware/appliance.
She then puts the two together to get the desired resulthow to get meaning out of Big Data. In the process, she also brings out the capabilities of the R programming language, which is mainly used in the area of statistical computing, graphics, and advanced analytics.
Her easy-to-read practical style of writing with real examples shows her depth of understanding of this subject. The book would be very useful for both data scientists (who need to learn the computing side and technologies to understand) and also for those who aspire to learn data science.
V. Laxmikanth
Managing Director
Broadridge Financial Solutions (India) Private Limited
www.broadridge.com
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.
Acknowledgement
It was a pleasure to work with Packt Publishing on this project. Packt has been most accommodating, extremely quick, and responsive to all requests.
I am deeply grateful to Broadridge for providing me the platform to explore and build expertise in Big Data technologies. My greatest gratitude to Laxmikanth V. (Managing Director, Broadridge) and Niladri Ray (Executive Vice President, Broadridge) for all the trust, freedom, and confidence in me.
Thanks to my parents for having relentlessly encouraged me to explore any and every subject that interested me.
Authors usually thank their spouses for their "patience and support" or words to that effect. Unless one has lived through the actual experience, one cannot fully comprehend how true this is. Over the last ten years, Kalyan has endured what must have seemed like a nearly continuous stream of whining punctuated by occasional outbursts of exhilaration and grandiosityall of which before the background of the self-absorbed attitude of a typical author. His patience and support were unfailing.
Last but not least, my love, my daughter, my angel, Nikita, who has been my continuous drive. Without her being as accommodative as she was, this book wouldn't have been possible.