Download Data Mining Techniques: For Marketing, Sales, and Customer by Gordon S. Linoff, Michael J. A. Berry PDF

By Gordon S. Linoff, Michael J. A. Berry

Very good insurance of varied elements of knowledge mining. well known as a textbook (reason for purchase). lots of portraits and illustrations; written in transparent and simply understood English.

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Additional resources for Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management

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Data Is Being Warehoused Not only is a large amount of data being produced, but also, more and more often, it is being extracted from the operational billing, reservations, claims processing, and order entry systems where it is generated and then fed into a data warehouse to become part of the corporate memory. Data warehousing brings together data from many different sources in a common format with consistent definitions for keys and fields. It is generally not possible (and certainly not advisable) to perform computer- and input/ output (I/O)–intensive data mining operations on an operational system that the business depends on to survive.

Data mining can help make more informed decisions. It can suggest tests to make. Ultimately, though, the business needs to make the decision. What Is Data Mining? Data mining, as we use the term, is the exploration and analysis of large quan­ tities of data in order to discover meaningful patterns and rules. For the pur­ poses of this book, we assume that the goal of data mining is to allow a corporation to improve its marketing, sales, and customer support operations through a better understanding of its customers.

Her father has moved to nearby Cambridge. But one thing has not changed. The author is still a loyal customer of the Wine Cask, where some of the same people who first introduced him to cheap Algerian reds in 1978 and later to the wine-growing regions of France are now helping him to explore Italy and Germany. After a quarter of a century, they still have a loyal customer. That loyalty is no accident. Dan and Steve at the Wine Cask learn the tastes of their customers and their price ranges. When asked for advice, their response will be based on their accumulated knowledge of that customer’s tastes and budgets as well as on their knowledge of their stock.

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