Big Data at Work: Dispelling the Myths, Uncovering the Opportunities Author: Thomas H. Davenport | Language: English | ISBN:
B00HSNMG90 | Format: EPUB
Big Data at Work: Dispelling the Myths, Uncovering the Opportunities Description
Go ahead, be skeptical about big data. The author was—at first.
When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind.
Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold.
This book will help you understand:
• Why big data is important to you and your organization
• What technology you need to manage it
• How big data could change your job, your company, and your industry
• How to hire, rent, or develop the kinds of people who make big data work
• The key success factors in implementing any big data project
• How big data is leading to a new approach to managing analytics
With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.
- File Size: 1287 KB
- Print Length: 240 pages
- Publisher: Harvard Business Review Press (February 4, 2014)
- Sold by: Amazon Digital Services, Inc.
- Language: English
- ASIN: B00HSNMG90
- Text-to-Speech: Enabled
X-Ray:
- Lending: Not Enabled
- Amazon Best Sellers Rank: #7,581 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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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 value
The book assiduously avoids using technical language, and as a result the book avoids answering some of the questions raised in readers' minds.
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