More Predictive Analytics

Author: Conrad Carlberg
Publisher: Que Publishing
ISBN: 9780134070933
Release Date: 2015-08-18
Genre: Computers

Accurate, practical Excel predictive analysis: powerful smoothing techniques for serious data crunchers! In More Predictive Analytics, Microsoft Excel® MVP Conrad Carlberg shows how to use intuitive smoothing techniques to make remarkably accurate predictions. You won’t have to write a line of code--all you need is Excel and this all-new, crystal-clear tutorial. Carlberg goes beyond his highly-praised Predictive Analytics, introducing proven methods for creating more specific, actionable forecasts. You’ll learn how to predict what customers will spend on a given product next year… project how many patients your hospital will admit next quarter… tease out the effects of seasonality (or patterns that recur over a day, year, or any other period)… distinguish real trends from mere “noise.” Drawing on more than 20 years of experience, Carlberg helps you master powerful techniques such as autocorrelation, differencing, Holt-Winters, backcasting, polynomial regression, exponential smoothing, and multiplicative modeling. Step by step, you’ll learn how to make the most of built-in Excel tools to gain far deeper insights from your data. To help you get better results faster, Carlberg provides downloadable Excel workbooks you can easily adapt for your own projects. If you’re ready to make better forecasts for better decision-making, you’re ready for More Predictive Analytics. Discover when and how to use smoothing instead of regression Test your data for trends and seasonality Compare sets of observations with the autocorrelation function Analyze trended time series with Excel’s Solver and Analysis ToolPak Use Holt's linear exponential smoothing to forecast the next level and trend, and extend forecasts further into the future Initialize your forecasts with a solid baseline Improve your initial forecasts with backcasting and optimization Fully reflect simple or complex seasonal patterns in your forecasts Account for sudden, unexpected changes in trends, from fads to new viral infections Use range names to control complex forecasting models more easily Compare additive and multiplicative models, and use the right model for each task

Predictive Analytics

Author: Conrad Carlberg
Publisher: Que Publishing
ISBN: 9780132967259
Release Date: 2012-07-02
Genre: Business & Economics

Excel predictive analytics for serious data crunchers! The movie Moneyball made predictive analytics famous: Now you can apply the same techniques to help your business win. You don’t need multimillion-dollar software: All the tools you need are available in Microsoft Excel, and all the knowledge and skills are right here, in this book! Microsoft Excel MVP Conrad Carlberg shows you how to use Excel predictive analytics to solve real-world problems in areas ranging from sales and marketing to operations. Carlberg offers unprecedented insight into building powerful, credible, and reliable forecasts, showing how to gain deep insights from Excel that would be difficult to uncover with costly tools such as SAS or SPSS. You’ll get an extensive collection of downloadable Excel workbooks you can easily adapt to your own unique requirements, plus VBA code—much of it open-source—to streamline several of this book’s most complex techniques. Step by step, you’ll build on Excel skills you already have, learning advanced techniques that can help you increase revenue, reduce costs, and improve productivity. By mastering predictive analytics, you’ll gain a powerful competitive advantage for your company and yourself. • Learn both the “how” and “why” of using data to make better tactical decisions • Choose the right analytics technique for each problem • Use Excel to capture live real-time data from diverse sources, including third-party websites • Use logistic regression to predict behaviors such as “will buy” versus “won’t buy” • Distinguish random data bounces from real, fundamental changes • Forecast time series with smoothing and regression • Construct more accurate predictions by using Solver to find maximum likelihood estimates • Manage huge numbers of variables and enormous datasets with principal components analysis and Varimax factor rotation • Apply ARIMA (Box-Jenkins) techniques to build better forecasts and understand their meaning

Decision Analytics

Author: Conrad Carlberg
Publisher: Que Publishing
ISBN: 9780133481686
Release Date: 2013-10-31
Genre: Business & Economics

Crunch Big Data to optimize marketing and more! Overwhelmed by all the Big Data now available to you? Not sure what questions to ask or how to ask them? Using Microsoft Excel and proven decision analytics techniques, you can distill all that data into manageable sets—and use them to optimize a wide variety of business and investment decisions. In Decision Analytics: Microsoft Excel, best selling statistics expert and consultant Conrad Carlberg will show you how—hands-on and step-by-step. Carlberg guides you through using decision analytics to segment customers (or anything else) into sensible and actionable groups and clusters. Next, you’ll learn practical ways to optimize a wide spectrum of decisions in business and beyond—from pricing to cross-selling, hiring to investments—even facial recognition software uses the techniques discussed in this book! Through realistic examples, Carlberg helps you understand the techniques and assumptions that underlie decision analytics and use simple Excel charts to intuitively grasp the results. With this foundation in place, you can perform your own analyses in Excel and work with results produced by advanced stats packages such as SAS and SPSS. This book comes with an extensive collection of downloadable Excel workbooks you can easily adapt to your own unique requirements, plus VBA code to streamline several of its most complex techniques. Classify data according to existing categories or naturally occurring clusters of predictor variables Cut massive numbers of variables and records down to size, so you can get the answers you really need Utilize cluster analysis to find patterns of similarity for market research and many other applications Learn how multiple discriminant analysis helps you classify cases Use MANOVA to decide whether groups differ on multivariate centroids Use principal components to explore data, find patterns, and identify latent factors Register your book for access to all sample workbooks, updates, and corrections as they become available at quepublishing.com/title/9780789751683.

big data work

Author: Thomas H. Davenport
Publisher: Vahlen
ISBN: 9783800648153
Release Date: 2014-10-15
Genre: Fiction

Big Data in Unternehmen. Dieses neue Buch gibt Managern ein umfassendes Verständnis dafür, welche Bedeutung Big Data für Unternehmen zukünftig haben wird und wie Big Data tatsächlich genutzt werden kann. Am Ende jedes Kapitels aktivieren Fragen, selbst nach Lösungen für eine erfolgreiche Implementierung und Nutzung von Big Data im eigenen Unternehmen zu suchen. Die Schwerpunkte - Warum Big Data für Sie und Ihr Unternehmen wichtig ist - Wie Big Data Ihre Arbeit, Ihr Unternehmen und Ihre Branche verändern - - wird - Entwicklung einer Big Data-Strategie - Der menschliche Aspekt von Big Data - Technologien für Big Data - Wie Sie erfolgreich mit Big Data arbeiten - Was Sie von Start-ups und Online-Unternehmen lernen können - Was Sie von großen Unternehmen lernen können: Big Data und Analytics 3.0 Der Experte Thomas H. Davenport ist Professor für Informationstechnologie und -management am Babson College und Forschungswissenschaftler am MIT Center for Digital Business. Zudem ist er Mitbegründer und Forschungsdirektor am International Institute for Analytics und Senior Berater von Deloitte Analytics.

Foundations of Predictive Analytics

Author: James Wu
Publisher: CRC Press
ISBN: 9781439869482
Release Date: 2012-02-15
Genre: Business & Economics

Drawing on the authors’ two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It also discusses a variety of practical topics that are frequently missing from similar texts. The book begins with the statistical and linear algebra/matrix foundation of modeling methods, from distributions to cumulant and copula functions to Cornish–Fisher expansion and other useful but hard-to-find statistical techniques. It then describes common and unusual linear methods as well as popular nonlinear modeling approaches, including additive models, trees, support vector machine, fuzzy systems, clustering, naïve Bayes, and neural nets. The authors go on to cover methodologies used in time series and forecasting, such as ARIMA, GARCH, and survival analysis. They also present a range of optimization techniques and explore several special topics, such as Dempster–Shafer theory. An in-depth collection of the most important fundamental material on predictive analytics, this self-contained book provides the necessary information for understanding various techniques for exploratory data analysis and modeling. It explains the algorithmic details behind each technique (including underlying assumptions and mathematical formulations) and shows how to prepare and encode data, select variables, use model goodness measures, normalize odds, and perform reject inference. Web Resource The book’s website at www.DataMinerXL.com offers the DataMinerXL software for building predictive models. The site also includes more examples and information on modeling.

Microsoft Excel 2013 Data Analysis and Business Modeling

Author: Wayne Winston
Publisher: Pearson Education
ISBN: 9780735681071
Release Date: 2014-01-15
Genre: Business & Economics

Master business modeling and analysis techniques with Microsoft Excel 2013, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide shows you how to use the latest Excel tools to integrate data from multiple tables—and how to effectively build a relational data source inside an Excel workbook. Solve real business problems with Excel—and sharpen your edge Summarize data with PivotTables and Descriptive Statistics Explore new trends in predictive and prescriptive analytics Use Excel Trend Curves, multiple regression, and exponential smoothing Master advanced Excel functions such as OFFSET and INDIRECT Delve into key financial, statistical, and time functions Make your charts more effective with the Power View tool Tame complex optimization problems with Excel Solver Run Monte Carlo simulations on stock prices and bidding models Apply important modeling tools such as the Inquire add-in

Business Intelligence in Microsoft SharePoint 2013

Author: Norm Warren
Publisher: Pearson Education
ISBN: 9780735675872
Release Date: 2013-05-15
Genre: Computers

Dive into the business intelligence features in SharePoint 2013—and use the right combination of tools to deliver compelling solutions. Take control of business intelligence (BI) with the tools offered by SharePoint 2013 and Microsoft SQL Server 2012. Led by a group of BI and SharePoint experts, you’ll get step-by-step instructions for understanding how to use these technologies best in specific BI scenarios—whether you’re a SharePoint administrator, SQL Server developer, or business analyst. Discover how to: Manage the entire BI lifecycle, from determining key performance indicators to building dashboards Use web-based Microsoft Excel services and publish workbooks on a SharePoint Server Mash up data from multiple sources and create Data Analysis Expressions (DAX) using PowerPivot Create data-driven diagrams that provide interactive processes and context with Microsoft Visio Services Use dashboards, scorecards, reports, and key performance indicators to monitor and analyze your business Use SharePoint to view BI reports side by side, no matter which tools were used to produced them

Predictive Analytics For Dummies

Author: Dr. Anasse Bari
Publisher: John Wiley & Sons
ISBN: 9781118729410
Release Date: 2014-03-06
Genre: Business & Economics

Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big Data Predictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more. Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businesses Helps readers see how to shepherd predictive analytics projects through their companies Explains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and more Covers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing data Also covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewhere Propose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies.

Fundamentals of Predictive Analytics with JMP Second Edition

Author: Ron Klimberg, PhD
Publisher: SAS Institute
ISBN: 9781629608013
Release Date: 2016-12-20
Genre: Computers

Written for students in undergraduate and graduate statistics courses, as well as for the practitioner who wants to make better decisions from data and models, this updated and expanded second edition of Fundamentals of Predictive Analytics with JMP® bridges the gap between courses on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining and predictive analytics. Going beyond the theoretical foundation, this book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis. First, this book teaches you to recognize when it is appropriate to use a tool, what variables and data are required, and what the results might be. Second, it teaches you how to interpret the results and then, step-by-step, how and where to perform and evaluate the analysis in JMP®. Using JMP® 13 and JMP® 13 Pro, this book offers the following new and enhanced features in an example-driven format: an add-in for Microsoft Excel Graph Builder dirty data visualization regression ANOVA logistic regression principal component analysis LASSO elastic net cluster analysis decision trees k-nearest neighbors neural networks bootstrap forests boosted trees text mining association rules model comparison With today's emphasis on business intelligence, business analytics, and predictive analytics, this second edition is invaluable to anyone who needs to expand his or her knowledge of statistics and to apply real-world, problem-solving analysis. This book is part of the SAS Press program.

Microsoft Business Intelligence Tools for Excel Analysts

Author: Michael Alexander
Publisher: John Wiley & Sons
ISBN: 9781118821565
Release Date: 2014-04-17
Genre: Computers

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.

Applied Insurance Analytics

Author: Patricia L Saporito
Publisher: FT Press
ISBN: 9780133760736
Release Date: 2014-06-16
Genre: Computers

Insurers: use analytics to drive far more value from your most important asset -- data! Today, many insurers radically underutilize their data, leaving them vulnerable to traditional and non-traditional competitors alike. Now, drawing on 25 years of industry experience, Patricia Saporito shows how to systematically leverage analytics to improve business performance and customer satisfaction throughout any insurance business. Applied Insurance Analytics demonstrates how to use analytics to systematically improve operations ranging from underwriting and risk management to claims. Even more important: it will help you drive more value everywhere by defining a focused enterprise-wide analytics strategy, and overcoming the challenges that stand in your way. Saporito helps you assess your current analytics maturity, choose the new applications that offer the most value, and master best practices from throughout the industry and beyond. Throughout, she helps you gain more value from data assets, technologies and tools you've already invested in. You'll find new case studies, practical tools, and easy templates for improving the "Analytics IQ" of your entire enterprise. For every insurance industry professional and manager concerned with analytics, including users, IT pros, sales/marketing specialists, and data scientists. This book will also be valuable to students in any MBA or other program focused on insurance or risk management, and to many students in IT or analytics-specific programs.

Lineare Algebra

Author: Gilbert Strang
Publisher: Springer-Verlag
ISBN: 9783642556319
Release Date: 2013-03-07
Genre: Mathematics

Diese Einführung in die lineare Algebra bietet einen sehr anschaulichen Zugang zum Thema. Die englische Originalausgabe wurde rasch zum Standardwerk in den Anfängerkursen des Massachusetts Institute of Technology sowie in vielen anderen nordamerikanischen Universitäten. Auch hierzulande ist dieses Buch als Grundstudiumsvorlesung für alle Studenten hervorragend lesbar. Darüber hinaus gibt es neue Impulse in der Mathematikausbildung und folgt dem Trend hin zu Anwendungen und Interdisziplinarität. Inhaltlich umfasst das Werk die Grundkenntnisse und die wichtigsten Anwendungen der linearen Algebra und eignet sich hervorragend für Studierende der Ingenieurwissenschaften, Naturwissenschaften, Mathematik und Informatik, die einen modernen Zugang zum Einsatz der linearen Algebra suchen. Ganz klar liegt hierbei der Schwerpunkt auf den Anwendungen, ohne dabei die mathematische Strenge zu vernachlässigen. Im Buch wird die jeweils zugrundeliegende Theorie mit zahlreichen Beispielen aus der Elektrotechnik, der Informatik, der Physik, Biologie und den Wirtschaftswissenschaften direkt verknüpft. Zahlreiche Aufgaben mit Lösungen runden das Werk ab.

Even You Can Learn Statistics and Analytics

Author: David M. Levine
Publisher: FT Press
ISBN: 9780133382686
Release Date: 2014-12-03
Genre: Business & Economics

Thought you couldn’t learn statistics? You can – and you will! Even You Can Learn Statistics and Analytics, Third Edition is the practical, up-to-date introduction to statistics – for everyone! Now fully updated for "big data" analytics and the newest applications, it'll teach you all the statistical techniques you’ll need for finance, marketing, quality, science, social science, and more – one easy step at a time. Simple jargon-free explanations help you understand every technique, and extensive practical examples and worked problems give you all the hands-on practice you'll need. This edition contains more practical examples than ever – all updated for the newest versions of Microsoft Excel. You'll find downloadable practice files, templates, data sets, and sample models – including complete solutions you can put right to work! Learn how to do all this, and more: Apply statistical techniques to analyze huge data sets and transform them into valuable knowledge Construct and interpret statistical charts and tables with Excel or OpenOffice.org Calc 3 Work with mean, median, mode, standard deviation, Z scores, skewness, and other descriptive statistics Use probability and probability distributions Work with sampling distributions and confidence intervals Test hypotheses with Z, t, chi-square, ANOVA, and other techniques Perform powerful regression analysis and modeling Use multiple regression to develop models that contain several independent variables Master specific statistical techniques for quality and Six Sigma programs Hate math? No sweat. You’ll be amazed at how little you need. Like math? Optional "Equation Blackboard" sections reveal the mathematical foundations of statistics right before your eyes. If you need to understand, evaluate, or use statistics in business, academia, or anywhere else, this is the book you've been searching for!

Introducing Microsoft Azure HDInsight

Author: Avkash Chauhan
Publisher: Microsoft Press
ISBN: 9780133965919
Release Date: 2014-06-12
Genre: Computers

Microsoft Azure HDInsight is Microsoft’s 100 percent compliant distribution of Apache Hadoop on Microsoft Azure. This means that standard Hadoop concepts and technologies apply, so learning the Hadoop stack helps you learn the HDInsight service. At the time of this writing, HDInsight (version 3.0) uses Hadoop version 2.2 and Hortonworks Data Platform 2.0. In Introducing Microsoft Azure HDInsight, we cover what big data really means, how you can use it to your advantage in your company or organization, and one of the services you can use to do that quickly–specifically, Microsoft’s HDInsight service. We start with an overview of big data and Hadoop, but we don’t emphasize only concepts in this book–we want you to jump in and get your hands dirty working with HDInsight in a practical way. To help you learn and even implement HDInsight right away, we focus on a specific use case that applies to almost any organization and demonstrate a process that you can follow along with. We also help you learn more. In the last chapter, we look ahead at the future of HDInsight and give you recommendations for self-learning so that you can dive deeper into important concepts and round out your education on working with big data.