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Microsoft Data Mining
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Book Synopsis Microsoft Data Mining by : Barry de Ville
Download or read book Microsoft Data Mining written by Barry de Ville and published by Digital Press. This book was released on 2001-05 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This guide teaches data mining from the perspective of IT professionals using Microsoft data management and e-commerce technologies. The book explains major new data mining capabilities in the forthcoming SQL Server 2000, Microsoft Commerce Server, and other products, and details the new Microsoft standard, "OLE DB for Data Mining".
Book Synopsis Data Mining for Business Analytics by : Galit Shmueli
Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2019-10-14 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
Book Synopsis Data Mining with Microsoft SQL Server 2008 by : Jamie MacLennan
Download or read book Data Mining with Microsoft SQL Server 2008 written by Jamie MacLennan and published by John Wiley & Sons. This book was released on 2011-03-10 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: Eine praxisorientierte Einführung in das Data Mining Toolset des SQL Server 2008 und die neuen Data Mining Add-Ins für Office 2007. Enthält detaillierte Erläuterungen und Beispiele zu allen neuen Data Mining Features des SQL Server 2008. Gibt präzise Anleitungen zum Arbeiten mit den wichtigsten Data Mining-Algorithmen, (Naive Bayes-, Decision Trees-, Time Series-, Sequence Clustering-, Association- und Neural Network-Algorithmus), zum Data Mining in OLAP Datenbanken und mit SQL Server Integration Services 2008. Die begleitende Website enthält den kompletten Quellcode zu den Beispielen aus dem Buch.
Book Synopsis Implementing Data Mining Algorithms in Microsoft SQL Server by : Claudio Luiz Curotto
Download or read book Implementing Data Mining Algorithms in Microsoft SQL Server written by Claudio Luiz Curotto and published by WIT Press. This book was released on 2005 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: "All source codes, as well as data sets used in computational experiments, are included in the accompanying CD-ROM." -- p. [xv]
Book Synopsis Data Mining with Microsoft SQL Server 2000 by : Claude Seidman
Download or read book Data Mining with Microsoft SQL Server 2000 written by Claude Seidman and published by . This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount of information stored in corporate databases is exploding exponentially. Data mining--finding meaningful patterns in all that data--can give any organization a competitive advantage. This book is the in-depth reference from Microsoft for anyone who wants to take full advantage of the powerful data-mining features in SQL Server 2000. It examines the SQL Server 2000 Analysis Services architecture and shows how data mining fits into its complete suite of information-extraction technologies. Then it demonstrates how to structure and mine large databases with the algorithms included with SQL Server 2000 to find nuggets of useful information. It even shows how to create a practice data-mining model using data downloaded from a database. Coverage includes: INTRODUCTION TO DATA MINING: What data mining is and isn't, plus important principles and definitions behind data-mining methodologies, including the role of data-mining models, statistics, and algorithms SQL SERVER 2000 ARCHITECTURE: How data mining fits into the SQL Server 2000 Analysis Services architecture and how it builds on the SQL Server 2000 relational database and its embedded online analytical processing (OLAP) engine DATA-MINING METHODS: How to choose the best data-mining method for the job--decision trees or clustering EASE OF USE FEATURES: How to use the Mining Model Wizard and the OLAP Mining Model Editor to simplify creating, training, and processing a model PROGRAMMING THE DATA-MINING SERVICES: How to use data-mining models and Data Transformation Services, PivotTable Services, decision-support objects (DSO), PERL, Visual Basic, Scripting Edition, XML, and other tools and languages to work with the data-mining engine
Book Synopsis Data Mining with SQL Server 2005 by : ZhaoHui Tang
Download or read book Data Mining with SQL Server 2005 written by ZhaoHui Tang and published by John Wiley & Sons. This book was released on 2005-10-03 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Your in-depth guide to using the new Microsoft data mining standard to solve today's business problems Concealed inside your data warehouse and data marts is a wealth of valuable information just waiting to be discovered. All you need are the right tools to extract that information and put it to use. Serving as your expert guide, this book shows you how to create and implement data mining applications that will find the hidden patterns from your historical datasets. The authors explore the core concepts of data mining as well as the latest trends. They then reveal the best practices in the field, utilizing the innovative features of SQL Server 2005 so that you can begin building your own successful data mining projects. You'll learn: The principal concepts of data mining How to work with the data mining algorithms included in SQL Server data mining How to use DMX-the data mining query language The XML for Analysis API The architecture of the SQL Server 2005 data mining component How to extend the SQL Server 2005 data mining platform by plugging in your own algorithms How to implement a data mining project using SQL Server Integration Services How to mine an OLAP cube How to build an online retail site with cross-selling features How to access SQL Server 2005 data mining features programmatically
Book Synopsis Learn Data Mining Through Excel by : Hong Zhou
Download or read book Learn Data Mining Through Excel written by Hong Zhou and published by Apress. This book was released on 2020-06-13 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use popular data mining techniques in Microsoft Excel to better understand machine learning methods. Software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help. Excel allows you to work with data in a transparent manner. When you open an Excel file, data is visible immediately and you can work with it directly. Intermediate results can be examined while you are conducting your mining task, offering a deeper understanding of how data is manipulated and results are obtained. These are critical aspects of the model construction process that are hidden in software tools and programming language packages. This book teaches you data mining through Excel. You will learn how Excel has an advantage in data mining when the data sets are not too large. It can give you a visual representation of data mining, building confidence in your results. You will go through every step manually, which offers not only an active learning experience, but teaches you how the mining process works and how to find the internal hidden patterns inside the data. What You Will Learn Comprehend data mining using a visual step-by-step approachBuild on a theoretical introduction of a data mining method, followed by an Excel implementationUnveil the mystery behind machine learning algorithms, making a complex topic accessible to everyoneBecome skilled in creative uses of Excel formulas and functionsObtain hands-on experience with data mining and Excel Who This Book Is For Anyone who is interested in learning data mining or machine learning, especially data science visual learners and people skilled in Excel, who would like to explore data science topics and/or expand their Excel skills. A basic or beginner level understanding of Excel is recommended.
Book Synopsis Data Mining for Business Intelligence by : Galit Shmueli
Download or read book Data Mining for Business Intelligence written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2011-09-28 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition " full of vivid and thought-provoking anecdotes needs to be read by anyone with a serious interest in research and marketing." —Research magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining a welcome addition to the literature." —computingreviews.com Incorporating a new focus on data visualization and time series forecasting, Data Mining for Business Intelligence, Second Edition continues to supply insightful, detailed guidance on fundamental data mining techniques. This new edition guides readers through the use of the Microsoft Office Excel add-in XLMiner for developing predictive models and techniques for describing and finding patterns in data. From clustering customers into market segments and finding the characteristics of frequent flyers to learning what items are purchased with other items, the authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods, including classification, prediction, and affinity analysis as well as data reduction, exploration, and visualization. The Second Edition now features: Three new chapters on time series forecasting, introducing popular business forecasting methods including moving average, exponential smoothing methods; regression-based models; and topics such as explanatory vs. predictive modeling, two-level models, and ensembles A revised chapter on data visualization that now features interactive visualization principles and added assignments that demonstrate interactive visualization in practice Separate chapters that each treat k-nearest neighbors and Naïve Bayes methods Summaries at the start of each chapter that supply an outline of key topics The book includes access to XLMiner, allowing readers to work hands-on with the provided data. Throughout the book, applications of the discussed topics focus on the business problem as motivation and avoid unnecessary statistical theory. Each chapter concludes with exercises that allow readers to assess their comprehension of the presented material. The final chapter includes a set of cases that require use of the different data mining techniques, and a related Web site features data sets, exercise solutions, PowerPoint slides, and case solutions. Data Mining for Business Intelligence, Second Edition is an excellent book for courses on data mining, forecasting, and decision support systems at the upper-undergraduate and graduate levels. It is also a one-of-a-kind resource for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.
Book Synopsis Data Mining With Microsoft Sql Server" 2000 Technical Reference by : Seidman
Download or read book Data Mining With Microsoft Sql Server" 2000 Technical Reference written by Seidman and published by . This book was released on with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pattern Recognition and Machine Learning by : Christopher M. Bishop
Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Book Synopsis Data Analysis Using SQL and Excel by : Gordon S. Linoff
Download or read book Data Analysis Using SQL and Excel written by Gordon S. Linoff and published by John Wiley & Sons. This book was released on 2010-09-16 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: Useful business analysis requires you to effectively transform data into actionable information. This book helps you use SQL and Excel to extract business information from relational databases and use that data to define business dimensions, store transactions about customers, produce results, and more. Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what the results should look like.
Book Synopsis Predictive Analytics with Microsoft Azure Machine Learning by : Valentine Fontama
Download or read book Predictive Analytics with Microsoft Azure Machine Learning written by Valentine Fontama and published by Apress. This book was released on 2014-11-25 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter. The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft.
Book Synopsis Microsoft Business Intelligence Tools for Excel Analysts by : Michael Alexander
Download or read book Microsoft Business Intelligence Tools for Excel Analysts written by Michael Alexander and published by John Wiley & Sons. This book was released on 2014-05-05 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridge the big data gap with Microsoft Business Intelligence Tools for Excel Analysts The distinction between departmental reporting done by business analysts with Excel and the enterprise reporting done by IT departments with SQL Server and SharePoint tools is more blurry now than ever before. With the introduction of robust new features like PowerPivot and Power View, it is essential for business analysts to get up to speed with big data tools that in the past have been reserved for IT professionals. Written by a team of Business Intelligence experts, Microsoft Business Intelligence Tools for Excel Analysts introduces business analysts to the rich toolset and reporting capabilities that can be leveraged to more effectively source and incorporate large datasets in their analytics while saving them time and simplifying the reporting process. Walks you step-by-step through important BI tools like PowerPivot, SQL Server, and SharePoint and shows you how to move data back and forth between these tools and Excel Shows you how to leverage relational databases, slice data into various views to gain different visibility perspectives, create eye-catching visualizations and dashboards, automate SQL Server data retrieval and integration, and publish dashboards and reports to the web Details how you can use SQL Server’s built-in functions to analyze large amounts of data, Excel pivot tables to access and report OLAP data, and PowerPivot to create powerful reporting mechanisms You’ll get on top of the Microsoft BI stack and all it can do to enhance Excel data analysis with this one-of-a-kind guide written for Excel analysts just like you.
Book Synopsis Applied Microsoft Analysis Services 2005 and Microsoft Business Intelligence Platform by : Teo Lachev
Download or read book Applied Microsoft Analysis Services 2005 and Microsoft Business Intelligence Platform written by Teo Lachev and published by Prologika Press. This book was released on 2005 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge is power! As its name suggests, the promise of Microsoft SQL Server Analysis Services 2005 is to promote better data analytics by giving information workers the right tool to analyze consistent, timely, and reliable data. Empowered with Analysis Services and Microsoft Business Intelligence Platform, you are well positioned to solve the perennial problem with data--that there is too much of it and finding the right information is often difficult, if not impossible. Applied Micrisoft Analysis Services 2005 shows database administrators and developers how to build complete OLAP solutions with Microsoft Analysis Services 2005 and Microsoft Business Intelligence Platform. Database administrators will learn how to design and manage sophisticated OLAP cubes that provide rich data analytics and data mining services. The book gives developers the necessary background to extend UDM with custom programming logic, in the form of MDX expressions, scripts and .NET code. It teaches them how to implement a wide range of reporting applications that integrate with Analysis Services, Reporting Services, and Microsoft Office. This book doesn't assume any prior experience with OLAP and Microsoft Analysis Services. It is designed as an easy-to-follow guide where each chapter builds upon the previous to implement the components of the innovative Unified Dimensional Model (UDM) in a chronological order. New concepts are introduced with step-by-step instructions and hands-on demos. What's Inside: o Design sophisticated UDM models o Build ETL processes with SSIS o Implement data mining tasks o Enrich UDM programmatically with MDX o Extend UDM with SSAS stored procedures o Create rich end-user model o Optimize Analysis Services storage and processing o Implement dynamic security o Build custom OLAP clients o Author standard and ad-hoc reports with SSRS o Build Office-based BI applications and dashboards o and much more
Book Synopsis Tabular Modeling in Microsoft SQL Server Analysis Services by : Marco Russo
Download or read book Tabular Modeling in Microsoft SQL Server Analysis Services written by Marco Russo and published by Microsoft Press. This book was released on 2017-04-12 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build agile and responsive business intelligence solutions Create a semantic model and analyze data using the tabular model in SQL Server 2016 Analysis Services to create corporate-level business intelligence (BI) solutions. Led by two BI experts, you will learn how to build, deploy, and query a tabular model by following detailed examples and best practices. This hands-on book shows you how to use the tabular model’s in-memory database to perform rapid analytics—whether you are new to Analysis Services or already familiar with its multidimensional model. Discover how to: • Determine when a tabular or multidimensional model is right for your project • Build a tabular model using SQL Server Data Tools in Microsoft Visual Studio 2015 • Integrate data from multiple sources into a single, coherent view of company information • Choose a data-modeling technique that meets your organization’s performance and usability requirements • Implement security by establishing administrative and data user roles • Define and implement partitioning strategies to reduce processing time • Use Tabular Model Scripting Language (TMSL) to execute and automate administrative tasks • Optimize your data model to reduce the memory footprint for VertiPaq • Choose between in-memory (VertiPaq) and pass-through (DirectQuery) engines for tabular models • Select the proper hardware and virtualization configurations • Deploy and manipulate tabular models from C# and PowerShell using AMO and TOM libraries Get code samples, including complete apps, at: https://aka.ms/tabular/downloads About This Book • For BI professionals who are new to SQL Server 2016 Analysis Services or already familiar with previous versions of the product, and who want the best reference for creating and maintaining tabular models. • Assumes basic familiarity with database design and business analytics concepts.
Book Synopsis Data Mining with Microsoft SQL Server 2000 by : Claude Seidman
Download or read book Data Mining with Microsoft SQL Server 2000 written by Claude Seidman and published by . This book was released on 2001 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Delivering Business Intelligence with Microsoft SQL Server 2005 by : Brian Larson
Download or read book Delivering Business Intelligence with Microsoft SQL Server 2005 written by Brian Larson and published by McGraw Hill Professional. This book was released on 2006-02-14 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transform disparate enterprise data into actionable business intelligence Put timely, mission-critical information in the hands of employees across your organization using Microsoft SQL Server 2005 and the comprehensive information in this unique resource. Delivering Business Intelligence with Microsoft SQL Server 2005 shows you, step-by-step, how to author, customize, and distribute information that will give your company the competitive edge. It's all right here--from data mining, warehousing, and scripting techniques to MDX queries, KPI analysis, and the all-new Unified Dimensional Model. Real-world examples, start-to-finish exercises, and downloadable code throughout illustrate all of the integration, analysis, and reporting capabilities of SQL Server 2005.
