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Understand Microsoft's dramatically updated new release of its premier toolset for business intelligence The first major update to Microsoft's state-of-the-art, complex toolset for business intelligence (BI) in years is now available and what better way to master it than with this detailed book from key members of the product's development team? If you're a database or data warehouse developer, this is the expert resource you need to build full-scale, multi-dimensional, database applications using Microsoft's new SQL Server 2012 Analysis Services and related tools. Discover how to solve real-world BI problems by leveraging a slew of powerful new Analysis Services features and capabilities. These include the new DAX language, which is a more user-friendly version of MDX; PowerPivot, a new tool for performing simplified analysis of data; BISM, Microsoft's new Business Intelligence Semantic Model; and much more. Serves as an authoritative guide to Microsoft's new SQL Server 2012 Analysis Services BI product and is written by key members of the Microsoft Analysis Services product development team Covers SQL Server 2012 Analysis Services, a major new release with a host of powerful new features and capabilities Topics include using the new DAX language, a simplified, more user-friendly version of MDX; PowerPivot, a new tool for performing simplified analysis of data; BISM, Microsoft's new Business Intelligence Semantic Model; and a new, yet-to-be-named BI reporting tool Explores real-world scenarios to help developers build comprehensive solutions Get thoroughly up to speed on this powerful new BI toolset with the timely and authoritative Professional Microsoft SQL Server 2012 Analysis Services with MDX.

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The visual way to get up to speed on Access 2010 It's one thing to gain access to Access. It's another thing entirely to figure out how to do all the things you want to do in Access, because the software is not all that intuitive. This full-color guide clearly shows you how to get the most out of Access 2010, including how to enter new records; create, edit, and design tables and forms; organize, analyze, and share data; generate concise reports; and much more. With pages of step-by-step instructions, graphics, and helpful advice, this is the visual learner's Access book-keep this on your desk and flip to what you need, any time! Explores the very latest features, functions, and tools of Access 2010, a database software tool that is part of the new Microsoft Office 2010 Teaches you how to enter new records and create, edit, and design tables and forms Explains how to organize, analyze, and share data; generate concise reports; add smart tags to tables, save backup copies of your data; and more Demonstrates through step-by-step instructions and numerous, full-color screen shots and graphics, so you can see exactly how to perform tasks This unparalleled book contains everything you need to know to use Access 2010 effectively.

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Harness the power of SQL Server, Microsoft’s high-performance database and data analysis software package, by accesing everything you need to know in Microsoft SQL Server 2008 Bible. Learn the best practices, tips, and tricks from this comprehensive tutorial and reference, which includes specific examples and sample code, with nearly every task demonstrated in both a graphical and SQL code method. Understand how to develop SQL Server databases and data connections, how to administer the SQL Server and keep databases performing optimally, and how to navigate all the new features of the 2008 release.

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Aimed at helping business and IT managers clearly communicate with each other, this helpful book addresses concerns straight-on and provides practical methods to building a collaborative data warehouse . You’ll get clear explanations of the goals and objectives of each stage of the data warehouse lifecycle while learning the roles that both business managers and technicians play at each stage. Discussions of the most critical decision points for success at each phase of the data warehouse lifecycle help you understand ways in which both business and IT management can make decisions that best meet unified objectives.

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Understand how to use the new features of Microsoft SQL Server 2008 for data mining by using the tools in Data Mining with Microsoft SQL Server 2008, which will show you how to use the SQL Server Data Mining Toolset with Office 2007 to mine and analyze data. Explore each of the major data mining algorithms, including naive bayes, decision trees, time series, clustering, association rules, and neural networks. Learn more about topics like mining OLAP databases, data mining with SQL Server Integration Services 2008, and using Microsoft data mining to solve business analysis problems.

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An easy-to-follow introduction to support vector machines This book provides an in-depth, easy-to-follow introduction to support vector machines drawing only from minimal, carefully motivated technical and mathematical background material. It begins with a cohesive discussion of machine learning and goes on to cover: Knowledge discovery environments Describing data mathematically Linear decision surfaces and functions Perceptron learning Maximum margin classifiers Support vector machines Elements of statistical learning theory Multi-class classification Regression with support vector machines Novelty detection Complemented with hands-on exercises, algorithm descriptions, and data sets, Knowledge Discovery with Support Vector Machines is an invaluable textbook for advanced undergraduate and graduate courses. It is also an excellent tutorial on support vector machines for professionals who are pursuing research in machine learning and related areas.

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Discover grid computing-how to successfully build, implement, and manage widely distributed computing architecture With technology budgets under increasing scrutiny and system architecture becoming more and more complex, many organizations are rethinking how they manage and use technology. Keeping a strong business focus, this publication clearly demonstrates that the current ways of tying applications to dedicated hardware are no longer viable in today's competitive, bottom line-oriented environment. This evolution in distributed computing is leading a paradigm shift in leveraging widely distributed architectures to get the most processing power per IT dollar. Presenting a solid foundation of data management issues and techniques, this practical book delves into grid architecture, services, practices, and much more, including: * Why businesses should adopt grid computing * How to master the fundamental concepts and programming techniques and apply them successfully to reach objectives * How to maximize the value of existing IT investments The author has tailored this publication for two distinct audiences. Business professionals will gain a better understanding of how grid computing improves productivity and performance, what impact it can have on their organization's bottom line, and the technical foundations necessary to discuss grid computing with their IT colleagues. Following the author's expert guidance and practical examples, IT professionals, architects, and developers will be equipped to initiate and carry out successful grid computing projects within their own organizations.

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Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification. Highlighting both underlying concepts and practical computational skills, Data Mining and Business Analytics with R begins with coverage of standard linear regression and the importance of parsimony in statistical modeling. The book includes important topics such as penalty-based variable selection (LASSO); logistic regression; regression and classification trees; clustering; principal components and partial least squares; and the analysis of text and network data. In addition, the book presents: • A thorough discussion and extensive demonstration of the theory behind the most useful data mining tools • Illustrations of how to use the outlined concepts in real-world situations • Readily available additional data sets and related R code allowing readers to apply their own analyses to the discussed materials • Numerous exercises to help readers with computing skills and deepen their understanding of the material Data Mining and Business Analytics with R is an excellent graduate-level textbook for courses on data mining and business analytics. The book is also a valuable reference for practitioners who collect and analyze data in the fields of finance, operations management, marketing, and the information sciences.

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Improve the performance of relational databases with indexes designed for today's hardware Over the last few years, hardware and software have advanced beyond all recognition, so it's hardly surprising that relational database performance now receives much less attention. Unfortunately, the reality is that the improved hardware hasn't kept pace with the ever-increasing quantity of data processed today. Although disk packing densities have increased enormously, making storage costs extremely low and sequential read very fast, random reads are still painfully slow. Many of the old design recommendations are therefore no longer valid-the optimal point of indexing has come a long way. Consequently many of the old problems haven't actually gone away-they have simply changed their appearance. This book provides an easy but effective approach to the design of indexes and tables. Using lots of examples and case studies, the authors describe how the DB2, Oracle, and SQL Server optimizers determine how to access data, and how CPU and response times for the resulting access paths can be quickly estimated. This enables comparisons to be made of the various designs, and helps you choose available choices for the most appropriate design. This book is intended for anyone who wants to understand the issues of SQL performance or how to design tables and indexes effectively. With this title, readers with many years of experience of relational systems will be able to better grasp the implications that have been brought into play by the introduction of new hardware.

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Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Written by Dr. Gabor Szabo, a Senior Data Scientist at Twitter, and Dr. Oscar Boykin, a Software Engineer at Twitter, Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses. Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media – examples include Twitter, Facebook, Pinterest, Wikipedia, Reddit, Flickr, Web hyperlinks, and other rich data sources. In it, you will learn: The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions Szabo and Boykin wrote this book to provide businesses with the competitive advantage they need to harness the rich data that is available from social media platforms.

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