Juli 27, 2012
Free Ebook , by Thomas H. Davenport
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, by Thomas H. Davenport
Free Ebook , by Thomas H. Davenport
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Product details
File Size: 1567 KB
Print Length: 228 pages
Publisher: Harvard Business Review Press (February 4, 2014)
Publication Date: February 4, 2014
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B00HSNMG90
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Big data, at least today, requires some educated faith. ROI is difficult to define in advance--particularly when it involves new products and services or faster decisions, according to Thomas Davenport in this book. Nonetheless, some businesses are getting significant benefits from employing data scientists to work on Big Data, so it definitely seems to be something worth investigating.Although the idea of Big Data is not precisely defined, the characteristics of Big Data described by the author include unstructured formats, volume of greater than 100 terrabytes, existing in a constant flow rather than a static pool, analysed by machine learning rather than hypothesis, and intended for data-based products rather than internal decision support. These are trends rather than absolutes, as Big Data includes more conventional types of data as well.The key to deriving maximum advantage from Big Data seems to involve employing the smartest data scientists to analyse the data. Good data scientists are likely to be rare and expensive, given the ideal traits described by the author:* Understanding of big data technology architectures and coding* Improvisation, evidence-based decision making and action orientation* Strong communication and relationship skills, particularly in dealing with senior management* High level skills in statistics, visual analytics, machine learning, and analysis of unstructured data* Good business sense and focus on commercial valueThe book assiduously avoids using technical language, and as a result the book avoids answering some of the questions raised in readers' minds. For example, the author refers frequently to Hadoop as a preferred technology platform for Big Data, but never really explains how it differs from SQL databases, apart from the fact that it caters for unstructured data (but how?).The book describes some large businesses such as banks which are making use of Big Data, and some small businesses which are analysing Big Data and using it to create and sell useful information, but never really answers the questions of how a normal business which does not have internal Big Data can get some, or how they could benefit from it, other than by hiring really smart data scientists and hoping that they can think of a way to use Big Data to reduce costs, speed up business processes, or come up with new products or services.I found more useful ideas for the use of Big Data in Christopher Surdak's book Data Crush: How the Information Tidal Wave Is Driving New Business Opportunities, but this book does provide some interesting insights, particularly into the human elements of Big Data.
Post Read Quick Review:Because this is geared towards executives rather than day-to-day practitioners, the language and depth are a bit shallow. We do not go under the hood and discuss the exact functioning of MR and Hadoop, popular algorithms and analytic procedures, or exact mechanics behind machine learning. What you do get is a lot of anecdotal examples (very close to what other books would structural as case studies) around a set of topics in big data and executes rather well for a novice into ease into the domain. There are many books like this but what separates this one is that it is actually an enjoyable experience. The author is a seasoned writer and knows the subtle intangible to keep people engaged and wanted to get to the next paragraph. Thomas Davenport has been an executive level thought leader on big data for some time and it really comes through. He is able to share his experience working and learning from heads of many institutions and improve the famarility of the most cultural endowed with big data,This book? I recommend.
I don't have a technical or analytical background, but I recently became interested in topics like predictive analytics and data science, and I wanted to learn more about them. I hear the term "big data" used a lot, so I wanted to find out what it's all about.This book is an excellent introduction to big data. It explains what it is, how it's different from "traditional" data analytics, why it's important and also what you need to do in order to take advantage of it. It helped to expand my "big data vocabulary" by explaining a lot of basic terms that I've seen come up a lot but never fully understood. It also showed me that most people who I've heard use the term "big data" don't really know what it means; they just think that it means "a lot of data," and use it as a fancy buzzword.This book won't give you formulas; it will give you a lot of solid explanations of introductory topics. It was an excellent first step for my interests. It's also an easy read. Read at your leisure, and you'll finish in a few days.
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