Data Mining Solution

Data Mining: Building Competitive Advantage with CDROM by Robert Groth,

"Finally, here's a book that explains in plain English what data mining is data mining solution and how it's used to improve a company's bottom line . . . Groth takes a very complex data mining solution and vast field data mining solution and makes it comprehensible." Miguel A. Castro, Ph.D., President, Dovetail Solutions Data mining business solutions-practical, up-to-date, data mining solution and hands-on! With data mining, you can achieve competitive advantage from the data you've already paid to compile. Data Mining: Building Competitive Advantage shows you how. You won't just learn the theory data mining solution and concepts of data mining; you'll discover how to apply them-hands-on, through real applications! Coverage includes: Case studies in banking, finance, retail, healthcare, direct marketing, data mining solution and telecommunications The data mining process, start to finish Today's newest, most successful approaches data mining solution and algorithms Data mining pitfalls-and how to avoid them A close look at industry-leading tools from Angoss(TM) data mining solution and RightPoint(TM) Whether you're a manager, marketer, consultant, analyst, or database professional, Robert Groth will help you master data mining-and deliver all the competitive advantage it promises. About the CD-ROM The accompanying CD-ROM includes full trial editions of two of the world's leading desktop data mining tools, Angoss KnowledgeSEEKER(R) data mining solution and RightPoint DataCruncher.
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Data Preparation for Data Mining with CDROM by Dorian Pyle,

"Data Preparation for Data Mining addresses an issue unfortunately ignored by most authorities on data mining: data preparation. Thanks largely to its perceived difficulty, data preparation has traditionally taken a backseat to the more alluring question of how best to extract meaningful knowledge. But without adequate preparation of your data, the return on the resources invested in mining is certain to be disappointing. Dorian Pyle corrects this imbalance. A twenty-five-year veteran of what has become the data mining industry, Pyle shares his own successful data preparation methodology, offering both a conceptual overview for managers data mining solution and complete technical details for IT professionals. Apply his techniques data mining solution and watch your mining efforts pay off-in the form of improved performance, reduced distortion, data mining solution and more valuable results. On the enclosed CD-ROM, you'll find a suite of programs as C source code data mining solution and compiled into a command-line-driven toolkit. This code illustrates how the author's techniques can be applied to arrive at an automated preparation solution that works for you. Also included are demonstration versions of three commercial products that help with data preparation, along with sample data with which you can practice data mining solution and experiment. * Offers in-depth coverage of an essential but largely ignored subject. * Goes far beyond theory, leading you-step by step-through the author's own data preparation techniques. * Provides practical illustrations of the author's methodology using realistic sample data sets. * Includes algorithms you can apply directly to your own project, along with instructions for understanding when automation is possible data mining solution and whengreater intervention is required. * Explains how to identify data mining solution and correct data problems that may be present in your application. * Prepares miners, helping them head into preparation with a better understanding of data sets data mining solution and their limitations.
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Data mining - Data mining, also known as knowledge-discovery in databases (KDD), is the practice of automatically searching large stores of data for patterns. To do this, data mining uses computational techniques from statistics, machine learning and pattern recognition.

Data stream mining - Data stream mining is the process of extracting knowledge structures from continuous, rapid data records. Examples of data streams include computer network traffic, phone conversations, ATM transactions, web searches and sensor data.

Data Mining Extensions - Data Mining Extensions (DMX) is a query language for Data Mining Models, much like SQL is a query language for relational databases and MDX is a query language for OLAP databases. DMX syntax is more similar to SQL then MDX.

Java Data Mining - Java Data Mining (JDM) is a standard Java API for developing data mining applications and tools. This standard was developed under the Java Community Process.

dataminingsolution

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'Data Storage Products' - 'Data Storage Products' Storage Networks Explained Storage Networks Explained has much to recommend it. a rarity in the literature of digital data storage a complete exposition of both the base subject matter 'data storage products' and its applications, which at the same time offers a level of readability making it suitable as an introduction to the subject. Storage Networks Explained is also flexible. It can be read cover-to-cover, browsed, or used as a reference. I recommend Storage Networks Explained as an essential component of any active information technology library. Paul Massiglia , Technical Director, VERITAS Software Corporation Storage networks will become a basic technology ...

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