Search Results for "business-analytics-using-sas-enterprise-guide-and-sas-enterprise-miner-a-beginner-s-guide"

Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner

Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner

A Beginner's Guide

  • Author: Olivia Parr-Rud
  • Publisher: SAS Institute
  • ISBN: 1629593281
  • Category: Mathematics
  • Page: 182
  • View: 1716
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This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. Today’s businesses increasingly use data to drive decisions that keep them competitive. Especially with the influx of big data, the importance of data analysis to improve every dimension of business cannot be overstated. Data analysts are therefore in demand; however, many hires and prospective hires, although talented with respect to business and statistics, lack the know-how to perform business analytics with advanced statistical software. Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner is a beginner’s guide with clear, illustrated, step-by-step instructions that will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. This book is part of the SAS Press program.

Basic Statistics Using SAS Enterprise Guide

Basic Statistics Using SAS Enterprise Guide

A Primer

  • Author: Geoff Der,Brian Everitt
  • Publisher: SAS Institute
  • ISBN: 1599947153
  • Category: Computers
  • Page: 240
  • View: 4908
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This example-rich guide shows you how to conduct a wide range of statistical analyses with no SAS programming required. For each analysis, one or more real data sets, a brief introduction of the technique, and a clear explanation of the SAS Enterprise Guide output are provided.

Statistics Using SAS Enterprise Guide

Statistics Using SAS Enterprise Guide

  • Author: James B. Davis, Ph.D.
  • Publisher: SAS Institute
  • ISBN: 1599947242
  • Category: Computers
  • Page: 785
  • View: 2510
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Discover how easy it is to perform statistical analysis using the power of SAS Enterprise Guide. Suitable for students new to statistics and to SAS, as well as for experienced professionals, James Davis's Statistics Using SAS Enterprise Guide provides an introduction to the basics of SAS Enterprise Guide and to statistics. Early chapters in this easy-to-follow book address topics such as how to work with data sets (including SAS data sets, data sets in Microsoft Excel, and other formats) and how to perform queries. A separate chapter on descriptive statistics offers a wide range of techniques and multiple presentation options. Later chapters provide detailed discussions (without calculus) of statistical theory and step-by-step examples that illustrate how to apply the appropriate SAS Enterprise Guide tasks, including both complete output and thorough analyses of the results. These chapters present examples of one-sample inference, two-sample inference, analysis of variance, correlation and regression, and table analysis

Data Mining Using SAS Enterprise Miner

Data Mining Using SAS Enterprise Miner

  • Author: Randall Matignon,SAS Institute
  • Publisher: John Wiley & Sons
  • ISBN: 0470149019
  • Category: Computers
  • Page: 564
  • View: 6133
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The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner. The Sample, Explore, Modify, Model, and Assess (SEMMA) methodology of SAS Enterprise Miner is an extremely valuable analytical tool for making critical business and marketing decisions. Until now, there has been no single, authoritative book that explores every node relationship and pattern that is a part of the Enterprise Miner software with regard to SEMMA design and data mining analysis. Data Mining Using SAS Enterprise Miner introduces readers to a wide variety of data mining techniques and explains the purpose of-and reasoning behind-every node that is a part of the Enterprise Miner software. Each chapter begins with a short introduction to the assortment of statistics that is generated from the various nodes in SAS Enterprise Miner v4.3, followed by detailed explanations of configuration settings that are located within each node. Features of the book include: The exploration of node relationships and patterns using data from an assortment of computations, charts, and graphs commonly used in SAS procedures A step-by-step approach to each node discussion, along with an assortment of illustrations that acquaint the reader with the SAS Enterprise Miner working environment Descriptive detail of the powerful Score node and associated SAS code, which showcases the important of managing, editing, executing, and creating custom-designed Score code for the benefit of fair and comprehensive business decision-making Complete coverage of the wide variety of statistical techniques that can be performed using the SEMMA nodes An accompanying Web site that provides downloadable Score code, training code, and data sets for further implementation, manipulation, and interpretation as well as SAS/IML software programming code This book is a well-crafted study guide on the various methods employed to randomly sample, partition, graph, transform, filter, impute, replace, cluster, and process data as well as interactively group and iteratively process data while performing a wide variety of modeling techniques within the process flow of the SAS Enterprise Miner software. Data Mining Using SAS Enterprise Miner is suitable as a supplemental text for advanced undergraduate and graduate students of statistics and computer science and is also an invaluable, all-encompassing guide to data mining for novice statisticians and experts alike.

Data Analysis Using SAS Enterprise Guide

Data Analysis Using SAS Enterprise Guide

  • Author: Lawrence S. Meyers,Glenn Gamst,A. J. Guarino
  • Publisher: Cambridge University Press
  • ISBN: 0521112680
  • Category: Business & Economics
  • Page: 378
  • View: 6374
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This book presents the basic procedures for utilizing SAS Enterprise Guide to analyze statistical data. SAS Enterprise Guide is a graphical user interface (point and click) to the main SAS application. Each chapter contains a brief conceptual overview and then guides the reader through concrete step-by-step examples to complete the analyses. The eleven sections of the book cover a wide range of statistical procedures including descriptive statistics, correlation and simple regression, t tests, one-way chi square, data transformations, multiple regression, analysis of variance, analysis of covariance, multivariate analysis of variance, factor analysis, and canonical correlation analysis. Designed to be used either as a stand-alone resource or as an accompaniment to a statistics course, the book offers a smooth path to statistical analysis with SAS Enterprise Guide for advanced undergraduate and beginning graduate students, as well as professionals in psychology, education, business, health, social work, sociology, and many other fields.

SAS For Dummies

SAS For Dummies

  • Author: Stephen McDaniel,Chris Hemedinger
  • Publisher: John Wiley & Sons
  • ISBN: 9781118044018
  • Category: Computers
  • Page: 408
  • View: 3124
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Created in partnership with SAS, this book explores SAS, a business intelligence software that can be used in any business setting or enterprise for data delivery, reporting, data mining, forecasting, statistical analysis, and more SAS employee and technologist Stephen McDaniel combines real-world expertise and a friendly writing style to introduce readers to SAS basics Covers crucial topics such as getting various types of data into the software, producing reports, working with the data, basic SAS programming, macros, and working with SAS and databases

Getting Started with SAS Enterprise Miner 12.3

Getting Started with SAS Enterprise Miner 12.3

  • Author: SAS Institute
  • Publisher: SAS Institute
  • ISBN: 1612907717
  • Category: Computers
  • Page: 80
  • View: 2210
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Introduces the core functionality of SAS Enterprise Miner 12.3 on SAS 9.4 and shows how to perform basic data-mining tasks. Provides step-by-step examples that create a complete process-flow diagram including graphic results.

Data Mining Cookbook

Data Mining Cookbook

Modeling Data for Marketing, Risk, and Customer Relationship Management

  • Author: Olivia Parr Rud
  • Publisher: John Wiley & Sons
  • ISBN: 0471437514
  • Category: Computers
  • Page: 416
  • View: 354
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Increase profits and reduce costs by utilizing this collection of models of the most commonly asked data mining questions In order to find new ways to improve customer sales and support, and as well as manage risk, business managers must be able to mine company databases. This book provides a step-by-step guide to creating and implementing models of the most commonly asked data mining questions. Readers will learn how to prepare data to mine, and develop accurate data mining questions. The author, who has over ten years of data mining experience, also provides actual tested models of specific data mining questions for marketing, sales, customer service and retention, and risk management. A CD-ROM, sold separately, provides these models for reader use.

Predictive Modeling with SAS Enterprise Miner

Predictive Modeling with SAS Enterprise Miner

Practical Solutions for Business Applications, Third Edition

  • Author: Kattamuri S. Sarma
  • Publisher: SAS Institute
  • ISBN: 1635260388
  • Category: Computers
  • Page: 574
  • View: 481
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A step-by-step guide to predictive modeling! Kattamuri Sarma's Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Third Edition, will show you how to develop and test predictive models quickly using SAS Enterprise Miner. Using realistic data, the book explains complex methods in a simple and practical way to readers from different backgrounds and industries. Incorporating the latest version of Enterprise Miner, this third edition also expands the section on time series. Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. Topics covered include logistic regression, regression, decision trees, neural networks, variable clustering, observation clustering, data imputation, binning, data exploration, variable selection, variable transformation, and much more, including analysis of textual data. Develop predictive models quickly, learn how to test numerous models and compare the results, gain an in-depth understanding of predictive models and multivariate methods, and discover how to do in-depth analysis. Do it all with Predictive Modeling with SAS Enterprise Miner!

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications

  • Author: Robert Nisbet,Gary Miner,Ken Yale
  • Publisher: Elsevier
  • ISBN: 0124166458
  • Category: Mathematics
  • Page: 822
  • View: 961
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Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Decision Trees for Analytics Using SAS Enterprise Miner

Decision Trees for Analytics Using SAS Enterprise Miner

  • Author: Barry de Ville,Padraic Neville
  • Publisher: SAS Institute
  • ISBN: 1629591009
  • Category: Mathematics
  • Page: 268
  • View: 3287
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Decision Trees for Analytics Using SAS Enterprise Miner is the most comprehensive treatment of decision tree theory, use, and applications available in one easy-to-access place. This book illustrates the application and operation of decision trees in business intelligence, data mining, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements data mining approaches such as regression, as well as other business intelligence applications that incorporate tabular reports, OLAP, or multidimensional cubes. An expanded and enhanced release of Decision Trees for Business Intelligence and Data Mining Using SAS Enterprise Miner, this book adds up-to-date treatments of boosting and high-performance forest approaches and rule induction. There is a dedicated section on the most recent findings related to bias reduction in variable selection. It provides an exhaustive treatment of the end-to-end process of decision tree construction and the respective considerations and algorithms, and it includes discussions of key issues in decision tree practice. Analysts who have an introductory understanding of data mining and who are looking for a more advanced, in-depth look at the theory and methods of a decision tree approach to business intelligence and data mining will benefit from this book. This book is part of the SAS Press program.

Statistical Programming in SAS

Statistical Programming in SAS

  • Author: A. John Bailer
  • Publisher: SAS Institute
  • ISBN: 9781607645047
  • Category: Computers
  • Page: 460
  • View: 6119
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In this guide, the author integrates SAS tools with interesting statistical applications and uses SAS 9.2 as a platform to introduce programming ideas for statistical analysis, data management, and data display and simulation.

An Introduction to SAS Visual Analytics

An Introduction to SAS Visual Analytics

How to Explore Numbers, Design Reports, and Gain Insight into Your Data

  • Author: Tricia Aanderud,Rob Collum,Ryan Kumpfmiller
  • Publisher: SAS Institute
  • ISBN: 1635260426
  • Category: Computers
  • Page: 294
  • View: 9097
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When it comes to business intelligence and analytical capabilities, SAS Visual Analytics is the premier solution for data discovery, visualization, and reporting. An Introduction to SAS Visual Analytics will show you how to make sense of your complex data with the goal of leading you to smarter, data-driven decisions without having to write a single line of code – unless you want to! You will be able to use SAS Visual Analytics to access, prepare, and present your data to anyone anywhere in the world. SAS Visual Analytics automatically highlights key relationships, outliers, clusters, trends and more. These abilities will guide you to critical insights that inspire action from your data. With this book, you will become proficient using SAS Visual Analytics to present data and results in customizable, robust visualizations, as well as guided analyses through auto-charting. With interactive dashboards, charts, and reports, you will create visualizations which convey clear and actionable insights for any size and type of data. This book largely focuses on the version of SAS Visual Analytics on SAS 9.4, although it is available on both 9.4 and SAS Viya platforms. Each version is considered the latest release, with subsequent releases planned to continue on each platform; hence, the Viya version works similarly to the 9.4 version and will look familiar. This book covers new features of each and important differences between the two. With this book, you will learn how to: Build your first report using the SAS Visual Analytics Designer Prepare a dashboard and determine the best layout Effectively use geo-spatial objects to add location analytics to reports Understand and use the elements of data visualizations Prepare and load your data with the SAS Visual Analytics Data Builder Analyze data with a variety of options, including forecasting, word clouds, heat maps, correlation matrix, and more Understand administration activities to keep SAS Visual Analytics humming along Optimize your environment for considerations such as scalability, availability, and efficiency between components of your SAS software deployment and data providers

Text Mining and Analysis

Text Mining and Analysis

Practical Methods, Examples, and Case Studies Using SAS

  • Author: Dr. Goutam Chakraborty,Murali Pagolu,Satish Garla
  • Publisher: SAS Institute
  • ISBN: 1612907873
  • Category: Mathematics
  • Page: 340
  • View: 2399
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Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media. However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries. Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis. This book is part of the SAS Press program.

Segmentation and Lifetime Value Models Using SAS

Segmentation and Lifetime Value Models Using SAS

  • Author: Edward C. Malthouse
  • Publisher: SAS Institute
  • ISBN: 1612907067
  • Category: Mathematics
  • Page: 182
  • View: 9444
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Help your organization determine the value of its customer relationships with Segmentation and Lifetime Value Models Using SAS. This book contains a wealth of information that will help you perform analyses to identify your customers and make informed marketing investments. It answers core questions on customer relationship management (CRM), provides an overall framework for thinking about CRM, and offers real-world examples across a variety of industries. Edward C. Malthouse introduces you to a number of useful models, ranging from simple to more complicated examples, and discusses their applications. You'll learn about segmentation models for identifying groups of customers and about lifetime value models for estimating the future value of the segments. You'll learn how to prepare data and estimate models using Base SAS, SAS/STAT, SAS/IML, and SQL. Marketing analysts, CRM analysts, database managers, and anyone looking to address the challenges of allocating marketing resources to different customer groups will benefit from the concepts and exercises in this book. Analysts will learn how to approach unique business problems. Managers will gain a sense of what's possible and what to ask of their analytics departments. This book is part of the SAS Press program.

Introduction to Data Mining Using SAS Enterprise Miner

Introduction to Data Mining Using SAS Enterprise Miner

  • Author: Patricia B. Cerrito
  • Publisher: SAS Institute
  • ISBN: 1599943379
  • Category: Computers
  • Page: 468
  • View: 4412
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If you have an abundance of data, but no idea what to do with it, this book was written for you! Packed with examples from an array of industries, Introduction to Data Mining Using SAS Enterprise Miner provides you with excellent starting points and practical guidelines to begin data mining today. Author Patricia Cerrito encourages you to think of data mining as a process of exploration rather than as a collection of tools to investigate data. In that way, you choose the methods that will extract the most information from your data, and, while there are no right answers to investigating data sets, there are many questions that can be asked to produce meaningful results. Each answer then creates a path that helps you drill down to explore the data fully. It is up to you to determine what is of interest and what is important to analyze.

The Little SAS Book

The Little SAS Book

A Primer, Fifth Edition

  • Author: Lora D. Delwiche,Susan J. Slaughter
  • Publisher: SAS Institute
  • ISBN: 1612904009
  • Category: Computers
  • Page: 376
  • View: 5956
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A classic that just keeps getting better, The Little SAS Book is essential for anyone learning SAS programming. Lora Delwiche and Susan Slaughter offer a user-friendly approach so readers can quickly and easily learn the most commonly used features of the SAS language. Each topic is presented in a self-contained two-page layout complete with examples and graphics. The fifth edition has been completely updated to reflect the new default output introduced with SAS 9.3. In addition, there is a now a full chapter devoted to ODS Graphics including the SGPLOT and SGPANEL procedures. Other changes include expanded coverage of linguistic sorting and a new section on concatenating macro variables with other text. This book is a great tool for users of SAS 9.4 as well. This title belongs on every SAS programmer's bookshelf. It's a resource not just to get you started, but one you'll return to as you continue to improve your programming skills. This book is part of the SAS Press program.

Administrative Healthcare Data

Administrative Healthcare Data

A Guide to Its Origin, Content, and Application Using SAS

  • Author: Craig Dickstein,Renu Gehring
  • Publisher: SAS Institute
  • ISBN: 1629593818
  • Category: Mathematics
  • Page: 250
  • View: 8998
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Provides a concise yet complete foundational knowledge of the business of healthcare. Administrative Healthcare Data: A Guide to Its Origin, Content, and Application Using SAS explains the source and content of administrative healthcare data, which is the product of financial reimbursement for healthcare services. The book integrates the business knowledge of healthcare data with practical and pertinent case studies as shown in SAS Enterprise Guide. The book's blend of SAS programming and industry knowledge is unique. It illustrates concepts of administrative healthcare data with actual healthcare case studies. All applications are created with SAS Enterprise Guide or Base SAS and can be taken straight from the book and put to use immediately. Central topics addressed include key players in the healthcare industry and the roles they play; claim submission mechanisms used by different providers; medical claim content, both pre- and post-adjudication. Written for healthcare analysts regardless of their level of proficiency with SAS Enterprise Guide, SAS programming, or healthcare industry knowledge, Administrative Healthcare Data is a must-read for analysts new to the industry and a great review for experienced healthcare analysts. This book is part of the SAS Press program.

Credit Risk Analytics

Credit Risk Analytics

Measurement Techniques, Applications, and Examples in SAS

  • Author: Bart Baesens,Daniel Roesch,Harald Scheule
  • Publisher: John Wiley & Sons
  • ISBN: 1119143985
  • Category: Business & Economics
  • Page: 512
  • View: 1172
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The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.

Business Intelligence Success Factors

Business Intelligence Success Factors

Tools for Aligning Your Business in the Global Economy

  • Author: Olivia Parr Rud
  • Publisher: John Wiley & Sons
  • ISBN: 9780470488409
  • Category: Business & Economics
  • Page: 256
  • View: 6679
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Praise for Business Intelligence Success Factors: Tools for Aligning your business in the Global Economy "Olivia Parr Rud does a remarkable job of weaving together many topics in a strategic way. As 'quants,' we're fascinated with data and fact-based decision-making. But success only comes when you consider the human factor, especially effective communications. Making topics like evolutionary biology, complexity science, and systems thinking relevant for business success is a unique and compelling view. As Max Frisch said, 'We hired workers and human beings came instead.'" —Anne Milley, Senior Director, Technology Product Marketing, SAS "Business Intelligence Success Factors is a must-read for anyone implementing BI on an organizational level. This book explains the business landscape and the underlying reasons for our current volatility, offering clear guidance on navigating our information rich global economy." —Ron Powell, Editorial Director, Business Intelligence Network Transform challenges into opportunities with emerging Business Intelligence technologies Written by an expert in data mining and statistical analysis, this valuable resource unveils the connection between the increased use of BI and the need for new, proven theories and models in BI, as well as the guidance to implement them successfully in your organization. Are you ready to become adaptable? Learn how to harness today's rapidly evolving global economy with Business Intelligence Success Factors.