Author: SAS Institute
Publisher:
ISBN: 9781599948898
Category : Geographic information systems
Languages : en
Pages : 0
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Book Description
Provides detailed information about importing map data and preparing the spatial databases required to create geographic information systems using SAS/GIS software. Also contains the complete reference for the GIS procedure in SAS/GIS software.
Author: Tricia Aanderud
Publisher: SAS Institute
ISBN: 1635260442
Category : Computers
Languages : en
Pages : 294
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Book Description
Focusing on the version of SAS Visual Analytics on SAS 9.4, this thorough guide 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 ¿̐ư unless you want to. --
Author: Mike Zdeb
Publisher: SAS Press
ISBN: 9781590470930
Category : Cartography
Languages : en
Pages : 0
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Book Description
Bring your data to life and add meaning to your information with Maps Made Easy Using SAS. Abundant real-world examples and a tutorial approach help new users create maps easily and quickly. You will learn the basic mapping components, including map and response data sets as well as simple SAS/GRAPH statements. With in-depth examples you will move on to more advanced mapping techniques, such as annotating maps and producing customized maps and output. The process used to annotate maps is demystified and described in clear, easy-to-follow steps. You will produce data-driven, updatable maps in GIF format for use in Web-based presentations and other applications. Also presented are details on creating more complicated choropleth maps. These include maps that combine geographic areas with internal boundaries removed, maps that display multiple geographic areas, and clipped maps. Enhance your data presentations with this well-organized guide. This book is part of the SAS Press program.
Author: Sas Education
Publisher:
ISBN: 9781642954906
Category :
Languages : en
Pages : 110
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Book Description
Data visualization enables decision makers to see analytics presented visually so that they can grasp difficult concepts or identify new patterns. SAS offers several solutions for visualizing your data, many of which are powered by SAS Viya. This book includes four visualization solutions powered by SAS Viya: SAS Visual Analytics, SAS Visual Statistics, SAS Visual Text Analytics, and SAS Visual Investigator. SAS visualization software is designed for anyone in your organization who wants to use and derive insights from data-from influencers, decision makers, and analysts to statisticians and data scientists. Also available as a free e-book from sas.com/books.
Author: Matthew Windham
Publisher: SAS Institute
ISBN: 1635267099
Category : Computers
Languages : en
Pages : 193
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Book Description
Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data. This book covers the five critical elements of entity extraction, unstructured data, entity resolution, entity network mapping and analysis, and entity management. By following examples of how to apply processing to unstructured data, readers will derive tremendous long-term value from this book as they enhance the value they realize from SAS products.
Author: Charles DiMaggio
Publisher: Springer Science & Business Media
ISBN: 1461448549
Category : Mathematics
Languages : en
Pages : 266
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Book Description
This comprehensive text covers the use of SAS for epidemiology and public health research. Developed with students in mind and from their feedback, the text addresses this material in a straightforward manner with a multitude of examples. It is directly applicable to students and researchers in the fields of public health, biostatistics and epidemiology. Through a “hands on” approach to the use of SAS for a broad number of epidemiologic analyses, readers learn techniques for data entry and cleaning, categorical analysis, ANOVA, and linear regression and much more. Exercises utilizing real-world data sets are featured throughout the book. SAS screen shots demonstrate the steps for successful programming. SAS (Statistical Analysis System) is an integrated system of software products provided by the SAS institute, which is headquartered in California. It provides programmers and statisticians the ability to engage in many sophisticated statistical analyses and data retrieval and mining exercises. SAS is widely used in the fields of epidemiology and public health research, predominately due to its ability to reliably analyze very large administrative data sets, as well as more commonly encountered clinical trial and observational research data.
Author: Mamdouh Refaat
Publisher: Elsevier
ISBN: 0080491006
Category : Computers
Languages : en
Pages : 425
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Book Description
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.
Author: Arthur Li
Publisher: CRC Press
ISBN: 1466552387
Category : Mathematics
Languages : en
Pages : 278
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Book Description
To write an accomplished program in the DATA step of SAS®, programmers must understand programming logic and know how to implement and even create their own programming algorithm. Handbook of SAS® DATA Step Programming shows readers how best to manage and manipulate data by using the DATA step. The book helps novices avoid common mistakes resulting from a lack of understanding fundamental and unique SAS programming concepts. It explains that learning syntax does not solve all problems; rather, a thorough comprehension of SAS processing is needed for successful programming. The author also guides readers through a programming task. In most of the examples, the author first presents strategies and steps for solving the problem, then offers a solution, and finally gives a more detailed explanation of the solution. Understanding the DATA steps, particularly the program data vector (PDV), is critical to proper data manipulation and management in SAS. This book helps SAS programmers thoroughly grasp the concept of DATA step processing and write accurate programs in the DATA step. Numerous supporting materials, including data sets and programs used in the text, are available on the book’s CRC Press web page.
Author: Bart Baesens
Publisher: John Wiley & Sons
ISBN: 1119143985
Category : Business & Economics
Languages : en
Pages : 517
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Book Description
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.
Author: Troy Martin Hughes
Publisher: Createspace Independent Publishing Platform
ISBN: 9781726497732
Category :
Languages : en
Pages : 372
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Book Description
SAS(R) Data-Driven Development is the only comprehensive text that demonstrates how to build dynamic SAS software driven by control data. Data-driven design enables developers to create flexible, reusable software that adapts to diverse industries, organizations, and data sources because business rules, data mappings, formatting, report style, program logic, and other dynamic elements are maintained as external control data — not as static code. Data-driven design is the key to unlocking highly configurable, "codeless" software that developers, SAS administrators, end users, and other stakeholders can reuse and configure — without modifying one line of code! This text introduces high-level design concepts, patterns, and principles, after which real-world scenarios demonstrate SAS development best practices: Part I. Data-Driven Design: Learn how to harness procedural abstraction, data abstraction, iteration abstraction, software modularity, and data independence, with concepts drawn from object-oriented programming (OOP), master data management (MDM), table-driven design, and business rules engines. Part II. Control Data: Understand the limitless data structures that can drive SAS software, including parameters, configuration files, control tables, decision tables, SAS data sets, SAS arrays, and CSV, Excel, XML, and CSS files. Interoperability is modeled through control data that can be accessed by SAS and other applications. Throughout the text, requirements-based examples demonstrate data analysis, data modeling, data mapping, data governance, dynamic "traffic light" reporting, and other use cases. Examples contrast concrete, code-driven design with abstract, data-driven design to illustrate the clear advantages of the latter. Application of the SAS Macro Language often signifies the first milestone in a SAS practitioner's career — because macros facilitate flexible, reusable software. Data-driven design represents the next milestone and this text provides the guidebook for that incredible journey. Start your journey today!
