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Data Quality For Analytics Using Sas

Author: Gerhard Svolba
Publisher: SAS Institute
ISBN: 162959802X
Size: 21.90 MB
Format: PDF, Mobi
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Analytics offers many capabilities and options to measure and improve data quality, and SAS is perfectly suited to these tasks. Gerhard Svolba's Data Quality for Analytics Using SAS focuses on selecting the right data sources and ensuring data quantity, relevancy, and completeness. The book is made up of three parts. The first part, which is conceptual, defines data quality and contains text, definitions, explanations, and examples. The second part shows how the data quality status can be profiled and the ways that data quality can be improved with analytical methods. The final part details the consequences of poor data quality for predictive modeling and time series forecasting.

Visual Six Sigma

Author: Ian Cox
Publisher: John Wiley & Sons
ISBN: 1118905687
Size: 49.12 MB
Format: PDF, ePub, Docs
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Visual Six Sigma Second Edition will include a new chapter on data quality and its preparation for analysis, which is perhaps the greatest challenge to analysts. It consists of six case studies that will be updated and streamlined to include new features available in JMP 11 and JMP 11 Pro. All screen captures will reflect the new JMP interface and to improve their quality and presentation.

What S New In Sas 9 4

Author: SAS
Publisher: SAS Institute
ISBN: 1629609773
Size: 50.67 MB
Format: PDF, Kindle
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Gives you a quick, convenient overview of new functionality, enhanced features, and new products that you might use in SAS 9.4.

Data Preparation For Data Mining Using Sas

Author: Mamdouh Refaat
Publisher: Elsevier
ISBN: 9780080491004
Size: 41.14 MB
Format: PDF
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Are you a data mining analyst, who spends up to 80% of your time assuring data quality, then preparing that data for developing and deploying predictive models? And do you find lots of literature on data mining theory and concepts, but when it comes to practical advice on developing good mining views find little “how to information? And are you, like most analysts, preparing the data in SAS? This book is intended to fill this gap as your source of practical recipes. It introduces a framework for the process of data preparation for data mining, and presents the detailed implementation of each step in SAS. In addition, business applications of data mining modeling require you to deal with a large number of variables, typically hundreds if not thousands. Therefore, the book devotes several chapters to the methods of data transformation and variable selection. A complete framework for the data preparation process, including implementation details for each step. The complete SAS implementation code, which is readily usable by professional analysts and data miners. A unique and comprehensive approach for the treatment of missing values, optimal binning, and cardinality reduction. Assumes minimal proficiency in SAS and includes a quick-start chapter on writing SAS macros.

Business Analytics Principles Concepts And Applications With Sas

Author: Marc J. Schniederjans
Publisher: Pearson Education
ISBN: 0133989577
Size: 27.56 MB
Format: PDF, Mobi
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Learn everything you need to know to start using business analytics and integrating it throughout your organization. Business Analytics Principles, Concepts, and Applications with SAS brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making. Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning. Unlike most competitive guides, this text demonstrates the use of SAS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself. Business Analytics Principles, Concepts, and Applications with SAS will be a valuable resource for all beginning-to-intermediate level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.

Applied Health Analytics And Informatics Using Sas

Author: Joseph M. Woodside
Publisher: SAS Institute
ISBN: 1635266149
Size: 56.61 MB
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Leverage health data into insight! Applied Health Analytics and Informatics Using SAS describes health anamatics, a result of the intersection of data analytics and health informatics. Healthcare systems generate nearly a third of the world’s data, and analytics can help to eliminate medical errors, reduce readmissions, provide evidence-based care, demonstrate quality outcomes, and add cost-efficient care. This comprehensive textbook includes data analytics and health informatics concepts, along with applied experiential learning exercises and case studies using SAS Enterprise MinerTM within the healthcare industry setting. Topics covered include: Sampling and modeling health data – both structured and unstructured Exploring health data quality Developing health administration and health data assessment procedures Identifying future health trends Analyzing high-performance health data mining models Applied Health Analytics and Informatics Using SAS is intended for professionals, lifelong learners, senior-level undergraduates, graduate-level students in professional development courses, health informatics courses, health analytics courses, and specialized industry track courses. This textbook is accessible to a wide variety of backgrounds and specialty areas, including administrators, clinicians, and executives. This book is part of the SAS Press program.

Decision Trees For Analytics Using Sas Enterprise Miner

Author: Barry de Ville
Publisher: SAS Institute
ISBN: 1629591009
Size: 27.67 MB
Format: PDF, ePub, Mobi
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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.

Predictive Analytics Als Data Mining Verfahren In Der Industrie 4 0 Gute Daten Schlechte Daten

Author: Dennis Bartz
Publisher: GRIN Verlag
ISBN: 3668297401
Size: 18.52 MB
Format: PDF, Kindle
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Studienarbeit aus dem Jahr 2016 im Fachbereich BWL - Allgemeines, Note: 1,3, Universität des Saarlandes, Sprache: Deutsch, Abstract: Im Zeitalter der Industrie 4.0 werden permanent Daten gesammelt. Maschinen kommunizieren untereinander, Wearables prägen den Alltag und die gewonnenen Daten werden mittels diverser Analyseverfahren teils automatisiert ausgewertet. Im Rahmen von Datenanalysenmethoden gilt es zwischen deskriptiven, prädiktiven und präskriptiven Analyseverfahren zu unterscheiden. Der Fokus dieser Arbeit liegt dabei auf Predictive Analytics. Predictive Analytics wird als Data-Mining-Verfahren zur systematischen Erkennung bestimmter Muster auf Basis von historischen und gegenwärtigen Daten definiert, welche prognostische Ergebnisse zur Ableitung zukünftiger Handlungsempfehlungen bereitstellt. Durch die ubiquitäre Vernetzung von Informations- und Kommunikationstechnologie soll bis zum Jahr 2025 die Wirtschaft maßgeblich durch Predictive Analytics beeinflusst und sämtliche Aktivitäten innerhalb der Wertschöpfungskette nachhaltig verbessert werden. Inhalt der Arbeit: - Untersuchung von Predictive Analytics und der theoretischen Rahmenbedingungen; - Deskriptive Betrachtung des derzeitigen Einsatzes von Predictive Analytics in Unternehmen; - Tangieren gesetzlicher Restriktionen im Rahmen der Datensammlung; - Präskriptive Analyse über die Entwicklung, Akzeptanz sowie den künftigen Einsatz von Predictive Analytics in der Arbeitswelt 2025

Regressionsanalyse Mit Spss

Author: Christian FG Schendera
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 311036252X
Size: 31.50 MB
Format: PDF, ePub, Docs
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The book provides a broad understanding of regression analysis in SPSS using many practical examples. It illustrates frequent sources of error and offers detailed descriptions and information about SPSS functions and syntax.

Sas For Dummies

Author: Stephen McDaniel
Publisher: John Wiley & Sons
ISBN: 9780470642726
Size: 13.58 MB
Format: PDF
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The fun and easy way to learn to use this leading business intelligence tool Written by an author team who is directly involved with SAS, this easy-to-follow guide is fully updated for the latest release of SAS and covers just what you need to put this popular software to work in your business. SAS allows any business or enterprise to improve data delivery, analysis, reporting, movement across a company, data mining, forecasting, statistical analysis, and more. SAS For Dummies, 2nd Edition gives you the necessary background on what SAS can do for you and explains how to use the Enterprise Guide. SAS provides statistical and data analysis tools to help you deal with all kinds of data: operational, financial, performance, and more Places special emphasis on Enterprise Guide and other analytical tools, covering all commonly used features Covers all commonly used features and shows you the practical applications you can put to work in your business Explores how to get various types of data into the software and how to work with databases Covers producing reports and Web reporting tools, analytics, macros, and working with your data In the easy-to-follow, no-nonsense For Dummies format, SAS For Dummies gives you the knowledge and the confidence to get SAS working for your organization. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.