Predictive Analytics, Data Mining and Big Data: Myths, by Steven Finlay (auth.)

By Steven Finlay (auth.)

This in-depth advisor presents managers with a pretty good figuring out of knowledge and information tendencies, the possibilities that it will possibly supply to companies, and the hazards of those applied sciences. Written in an available kind, Steven Finlay offers a contextual roadmap for constructing suggestions that carry advantages to organizations.

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Extra info for Predictive Analytics, Data Mining and Big Data: Myths, Misconceptions and Methods

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All that remains to be done is to find the right customers to target and persuade them to buy. A Unique Selling Point (USP) for the wine store is that the company has exclusive access to a large supply of high-quality locally sourced wines that the national retailers don’t have, and which are already being sold in Booles’ stores. The biggest challenge is to identify which customers outside of the region to target, and then develop an appropriate marketing campaign to attract them to buy online.

8 The rest of the book I hope this introductory chapter has given you an insight into what Big Data and predictive analytics are, what (one type) of predictive model looks like and how models can be used to help organizations achieve their objectives. With regard to the rest of the book, Chapters 2–5 are very much about the application and usage of predictive models. Chapter 2 explains how models are used in organizations to drive decision making, and Chapter 3 discusses the analytics culture that needs to be in place if the benefits of predictive analytics are to be realized.

This does not mean human judgment is unimportant, but that were the data supports or refutes a particular view or idea you give it due consideration. Maintain a skilled analytical team that has the capacity to reach out to the business and communicate analytical solutions in ways that they understand. Have buy-in from the “front line” who must act upon the decisions that result from using predictive analytics to predict behaviors. So what this means is that the use of automated data driven decision making, using predictive analytics, must be accepted across the organization.

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