Using Sas Data Integration Studio To Build Data Marts From Enterprise Data Sources
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| Author | : SAS Institute |
| Publisher | : Sas Inst |
| Total Pages | : 393 |
| Release | : 2007 |
| Genre | : Computers |
| ISBN | : 9781599941981 |
This manual is a task-oriented introduction to the main features of SAS Data Integration Studio. SAS Data Integration Studio is a visual design tool that enables you to consolidate and manage enterprise data from a variety of source systems, applications, and technologies. The audience for this manual is users who are responsible for data integration and who have a working knowledge of Base SAS software. This title is also available online.
| Author | : Gerhard Svolba |
| Publisher | : SAS Institute |
| Total Pages | : 373 |
| Release | : 2006-11-27 |
| Genre | : Computers |
| ISBN | : 1629597902 |
Written for anyone involved in the data preparation process for analytics, Gerhard Svolba's Data Preparation for Analytics Using SAS offers practical advice in the form of SAS coding tips and tricks, and provides the reader with a conceptual background on data structures and considerations from a business point of view. The tasks addressed include viewing analytic data preparation in the context of its business environment, identifying the specifics of predictive modeling for data mart creation, understanding the concepts and considerations of data preparation for time series analysis, using various SAS procedures and SAS Enterprise Miner for scoring, creating meaningful derived variables for all data mart types, using powerful SAS macros to make changes among the various data mart structures, and more!
| Author | : Sas Education |
| Publisher | : |
| Total Pages | : 80 |
| Release | : 2019-06-14 |
| Genre | : |
| ISBN | : 9781642954838 |
This first book in the series covers how to access data files, libraries, and existing code in SAS Studio. You also learn about new procedures in SAS Viya, how to write new code, and how to use some of the pre-installed tasks that come with SAS Visual Data Mining and Machine Learning. In the last chapter, you learn how to use the features in SAS Data Preparation to perform data management tasks using SAS Data Explorer, SAS Data Studio, and SAS Lineage Viewer. Also available free as a PDF from sas.com/books.
| Author | : SAS Institute |
| Publisher | : Sas Inst |
| Total Pages | : 395 |
| Release | : 2007 |
| Genre | : Computers |
| ISBN | : 9781599943763 |
Explains how to administer the SAS Web applications that run in the middle tier of the SAS Intelligence Platform. The Web applications include the SAS Information Delivery Portal, SAS Web Report Studio, and SAS Web OLAP Viewer for Java.This guide describes the middle-tier environment, provides sample deployment scenarios, and explains how to configure the Web applications for optimal performance. The guide contains instructions for common administrative tasks, such as configuring trusted Web authentication, as well as instructions for administering the individual Web applications. For example, the guide explains how to add content to the SAS Information Delivery Portal and how to control access to that content. This title is also available online.
| Author | : Safeeullah Soomro |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 464 |
| Release | : 2010-04-01 |
| Genre | : Computers |
| ISBN | : 9533070927 |
This book is consisting of 24 chapters which are focusing on the basic and applied research regarding e‐learning systems. Authors made efforts to provide theoretical as well as practical approaches to solve open problems through their elite research work. This book increases knowledge in the following topics such as e‐learning, e‐Government, Data mining in e‐learning based systems, LMS systems, security in e‐learning based systems, surveys regarding teachers to use e‐learning systems, analysis of intelligent agents using e‐learning, assessment methods for e‐learning and barriers to use of effective e‐learning systems in education. Basically this book is an open platform for creative discussion for future e‐learning based systems which are essential to understand for the students, researchers, academic personals and industry related people to enhance their capabilities to capture new ideas and provides valuable solution to an international community.
| Author | : Babatunde O Odusami |
| Publisher | : SAS Institute |
| Total Pages | : 405 |
| Release | : 2024-06-14 |
| Genre | : Computers |
| ISBN | : 1685800157 |
Explore financial data science using SAS. Financial Data Science with SAS provides readers with a comprehensive explanation of the theoretical and practical implementation of the various types of analytical techniques and quantitative tools that are used in the financial services industry. This book shows readers how to implement data visualization, simulation, statistical predictive models, machine learning models, and financial optimizations using real-world examples in the SAS Analytics environment. Each chapter ends with practice exercises that include use case scenarios to allow readers to test their knowledge. Designed for university students and financial professionals interested in boosting their data science skills, Financial Data Science with SAS is an essential reference guide for understanding how data science is used in the financial services industry and for learning how to use SAS to solve complex business problems.
| Author | : Dr. Goutam Chakraborty |
| Publisher | : SAS Institute |
| Total Pages | : 340 |
| Release | : 2014-11-22 |
| Genre | : Computers |
| ISBN | : 162959086X |
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.
| Author | : Rick Wicklin |
| Publisher | : SAS Institute |
| Total Pages | : 363 |
| Release | : 2013 |
| Genre | : Computers |
| ISBN | : 1612903320 |
Data simulation is a fundamental technique in statistical programming and research. Rick Wicklin's Simulating Data with SAS brings together the most useful algorithms and the best programming techniques for efficient data simulation in an accessible how-to book for practicing statisticians and statistical programmers. This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques. It also covers simulating correlated data, data for regression models, spatial data, and data with given moments. It provides tips and techniques for beginning programmers, and offers libraries of functions for advanced practitioners. As the first book devoted to simulating data across a range of statistical applications, Simulating Data with SAS is an essential tool for programmers, analysts, researchers, and students who use SAS software. This book is part of the SAS Press program.
| Author | : SAS Institute Inc. |
| Publisher | : SAS Institute |
| Total Pages | : 309 |
| Release | : 2020-05-29 |
| Genre | : Computers |
| ISBN | : 1951685377 |
Master machine learning with SAS Viya! Machine learning can feel intimidating for new practitioners. Machine Learning with SAS Viya provides everything you need to know to get started with machine learning in SAS Viya, including decision trees, neural networks, and support vector machines. The analytics life cycle is covered from data preparation and discovery to deployment. Working with open-source code? Machine Learning with SAS Viya has you covered – step-by-step instructions are given on how to use SAS Model Manager tools with open source. SAS Model Studio features are highlighted to show how to carry out machine learning in SAS Viya. Demonstrations, practice tasks, and quizzes are included to help sharpen your skills. In this book, you will learn about: Supervised and unsupervised machine learning Data preparation and dealing with missing and unstructured data Model building and selection Improving and optimizing models Model deployment and monitoring performance
| Author | : W. H. Inmon |
| Publisher | : John Wiley & Sons |
| Total Pages | : 400 |
| Release | : 2002-03-14 |
| Genre | : Computers |
| ISBN | : 0471437506 |
The "father of data warehousing" incorporates the latesttechnologies into his blueprint for integrated decision supportsystems Today's corporate IT and data warehouse managers are required tomake a small army of technologies work together to ensure fast andaccurate information for business managers. Bill Inmon created theCorporate Information Factory to solve the needs ofthese managers. Since the First Edition, the design of the factoryhas grown and changed dramatically. This Second Edition, revisedand expanded by 40% with five new chapters, incorporates thesechanges. This step-by-step guide will enable readers to connecttheir legacy systems with the data warehouse and deal with a hostof new and changing technologies, including Web access mechanisms,e-commerce systems, ERP (Enterprise Resource Planning) systems. Thebook also looks closely at exploration and data mining servers foranalyzing customer behavior and departmental data marts forfinance, sales, and marketing.
