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Analyzing pools of big data can help organizations uncover valuable information about customers and other business insights -- but it can also turn into a wild-goose chase if the process isn't well managed. This three-part guide will benefit business intelligence and analytics managers, data scientists, business executives and other readers with real-life examples of successful big data analytics efforts and project management advice.
To get the big data ball rolling, we first take a look at two organizations in different industries -- one in healthcare, the other in banking -- taking unique approaches to big data initiatives. The differences between the two, and reasoning behind them, will provide IT professionals with a solid understanding of how to begin the conversation of implementation. Next, analyst Rick Sherman outlines the key steps big data analytics project managers must take in order to put their programs on the right path. We close with a case study about a Time Warner Cable executive who, dissatisfied with commonplace and commandeering tools such as Hadoop and NoSQL databases, decided to treat big data technologies as a complement rather than a rule. Access >>>
Table of contents
- Large companies take long view on big data programs
- Project managers must take the big data helm
- In evaluating big data tools, look at the bigger picture
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