End To End Data Science With Sas


End To End Data Science With Sas
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End To End Data Science With Sas


End To End Data Science With Sas
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Author : James Gearheart
language : en
Publisher: SAS Institute
Release Date : 2020-06-26

End To End Data Science With Sas written by James Gearheart and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-26 with Computers categories.


Learn data science concepts with real-world examples in SAS! End-to-End Data Science with SAS: A Hands-On Programming Guide provides clear and practical explanations of the data science environment, machine learning techniques, and the SAS programming knowledge necessary to develop machine learning models in any industry. The book covers concepts including understanding the business need, creating a modeling data set, linear regression, parametric classification models, and non-parametric classification models. Real-world business examples and example code are used to demonstrate each process step-by-step. Although a significant amount of background information and supporting mathematics are presented, the book is not structured as a textbook, but rather it is a user’s guide for the application of data science and machine learning in a business environment. Readers will learn how to think like a data scientist, wrangle messy data, choose a model, and evaluate the model’s effectiveness. New data scientists or professionals who want more experience with SAS will find this book to be an invaluable reference. Take your data science career to the next level by mastering SAS programming for machine learning models.



Sas Essentials


Sas Essentials
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Author : Alan C. Elliott
language : en
Publisher: John Wiley & Sons
Release Date : 2023-01-05

Sas Essentials written by Alan C. Elliott and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-05 with Education categories.


SAS ESSENTIALS Valuable step-by-step introduction to using SAS® statistical software as a foundational approach to data analysis and interpretation Presenting a straightforward introduction from the ground up, SAS® Essentials illustrates SAS using hands-on learning techniques and numerous real-world examples; keeping different experience levels in mind, the highly qualified author team has developed the book over 25 years of teaching introductory SAS courses. This book introduces data manipulation, statistical techniques, and the SAS programming language, including SAS macros, reporting results in tables, and factor analysis, as well as sections on character functions, variable manipulation, and merging, appending, and updating files. It features self-contained chapters to enhance the learning process and includes programming approaches for the latest version of the SAS platform. The Third Edition has been updated with expanded examples, a new chapter introducing PROC SQL as well as new end-of-chapter exercises. The Third Edition also includes a companion website with data sets, additional code, notes on SAS programming, functions, ODS, PROC SQL, and SAS Arrays, along with solutions for instructors. Specific sample topics covered in SAS® Essentials include: Getting data into SAS, reading, writing, and importing data, preparing data for analysis, preparing to use SAS procedures, and controlling output using ODS Techniques for creating, editing, and debugging SAS programs, cleaning up messy data sets, and manipulating data using character, time, and numeric functions Other essential computational skills that are utilized by business, government, and organizations alike, and DATA step for data management Using PROC to analyze data, including evaluating quantitative data, analyzing counts and tables, comparing means using T-Tests, correlation and regression, and analysis of variance, nonparametric analysis, logistic regression, factor analysis, and creating custom graphs and reports. SAS® Essentials is a fundamental study resource for professionals preparing for the SAS Base Certification Exam, as well as an ideal textbook for courses in statistics, data analytics, applied SAS programming, and statistical computer applications.



Big Data Analytics With Sas


Big Data Analytics With Sas
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Author : David Pope
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-11-23

Big Data Analytics With Sas written by David Pope and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-23 with Computers categories.


Leverage the capabilities of SAS to process and analyze Big Data About This Book Combine SAS with platforms such as Hadoop, SAP HANA, and Cloud Foundry-based platforms for effecient Big Data analytics Learn how to use the web browser-based SAS Studio and iPython Jupyter Notebook interfaces with SAS Practical, real-world examples on predictive modeling, forecasting, optimizing and reporting your Big Data analysis with SAS Who This Book Is For SAS professionals and data analysts who wish to perform analytics on Big Data using SAS to gain actionable insights will find this book to be very useful. If you are a data science professional looking to perform large-scale analytics with SAS, this book will also help you. A basic understanding of SAS will be helpful, but is not mandatory. What You Will Learn Configure a free version of SAS in order do hands-on exercises dealing with data management, analysis, and reporting. Understand the basic concepts of the SAS language which consists of the data step (for data preparation) and procedures (or PROCs) for analysis. Make use of the web browser based SAS Studio and iPython Jupyter Notebook interfaces for coding in the SAS, DS2, and FedSQL programming languages. Understand how the DS2 programming language plays an important role in Big Data preparation and analysis using SAS Integrate and work efficiently with Big Data platforms like Hadoop, SAP HANA, and cloud foundry based systems. In Detail SAS has been recognized by Money Magazine and Payscale as one of the top business skills to learn in order to advance one's career. Through innovative data management, analytics, and business intelligence software and services, SAS helps customers solve their business problems by allowing them to make better decisions faster. This book introduces the reader to the SAS and how they can use SAS to perform efficient analysis on any size data, including Big Data. The reader will learn how to prepare data for analysis, perform predictive, forecasting, and optimization analysis and then deploy or report on the results of these analyses. While performing the coding examples within this book the reader will learn how to use the web browser based SAS Studio and iPython Jupyter Notebook interfaces for working with SAS. Finally, the reader will learn how SAS's architecture is engineered and designed to scale up and/or out and be combined with the open source offerings such as Hadoop, Python, and R. By the end of this book, you will be able to clearly understand how you can efficiently analyze Big Data using SAS. Style and approach The book starts off by introducing the reader to SAS and the SAS programming language which provides data management, analytical, and reporting capabilities. Most chapters include hands on examples which highlights how SAS provides The Power to Know©. The reader will learn that if they are looking to perform large-scale data analysis that SAS provides an open platform engineered and designed to scale both up and out which allows the power of SAS to combine with open source offerings such as Hadoop, Python, and R.



Data Preparation For Analytics Using Sas


Data Preparation For Analytics Using Sas
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Author : Gerhard Svolba
language : en
Publisher: SAS Institute
Release Date : 2006-11-27

Data Preparation For Analytics Using Sas written by Gerhard Svolba and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-27 with Computers categories.


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!



Hands On Sas For Data Analysis


Hands On Sas For Data Analysis
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Author : Harish Gulati
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-09-27

Hands On Sas For Data Analysis written by Harish Gulati and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-27 with Computers categories.


Leverage the full potential of SAS to get unique, actionable insights from your data Key FeaturesBuild enterprise-class data solutions using SAS and become well-versed in SAS programmingWork with different data structures, and run SQL queries to manipulate your dataExplore essential concepts and techniques with practical examples to confidently pass the SAS certification examBook Description SAS is one of the leading enterprise tools in the world today when it comes to data management and analysis. It enables the fast and easy processing of data and helps you gain valuable business insights for effective decision-making. This book will serve as a comprehensive guide that will prepare you for the SAS certification exam. After a quick overview of the SAS architecture and components, the book will take you through the different approaches to importing and reading data from different sources using SAS. You will then cover SAS Base and 4GL, understanding data management and analysis, along with exploring SAS functions for data manipulation and transformation. Next, you'll discover SQL procedures and get up to speed on creating and validating queries. In the concluding chapters, you'll learn all about data visualization, right from creating bar charts and sample geographic maps through to assigning patterns and formats. In addition to this, the book will focus on macro programming and its advanced aspects. By the end of this book, you will be well versed in SAS programming and have the skills you need to easily handle and manage your data-related problems in SAS. What you will learnExplore a variety of SAS modules and packages for efficient data analysisUse SAS 4GL functions to manipulate, merge, sort, and transform dataGain useful insights into advanced PROC SQL options in SAS to interact with dataGet to grips with SAS Macro and define your own macros to share dataDiscover the different graphical libraries to shape and visualize data withApply the SAS Output Delivery System to prepare detailed reportsWho this book is for Budding or experienced data professionals who want to get started with SAS will benefit from this book. Those looking to prepare for the SAS certification exam will also find this book to be a useful resource. Some understanding of basic data management concepts will help you get the most out of this book.



Statistical Data Analysis Using Sas


Statistical Data Analysis Using Sas
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Author : Mervyn G. Marasinghe
language : en
Publisher: Springer
Release Date : 2018-04-12

Statistical Data Analysis Using Sas written by Mervyn G. Marasinghe and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-12 with Computers categories.


The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitable for a second course in applied statistics with every method explained using SAS analysis to illustrate a real-world problem. New to this edition: • Covers SAS v9.2 and incorporates new commands • Uses SAS ODS (output delivery system) for reproduction of tables and graphics output • Presents new commands needed to produce ODS output • All chapters rewritten for clarity • New and updated examples throughout • All SAS outputs are new and updated, including graphics • More exercises and problems • Completely new chapter on analysis of nonlinear and generalized linear models • Completely new appendix Mervyn G. Marasinghe, PhD, is Associate Professor Emeritus of Statistics at Iowa State University, where he has taught courses in statistical methods and statistical computing. Kenneth J. Koehler, PhD, is University Professor of Statistics at Iowa State University, where he teaches courses in statistical methodology at both graduate and undergraduate levels and primarily uses SAS to supplement his teaching.



Applying Data Science


Applying Data Science
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Author : Gerhard Svolba
language : en
Publisher: SAS Institute
Release Date : 2017-03-29

Applying Data Science written by Gerhard Svolba and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-29 with Computers categories.


See how data science can answer the questions your business faces! Applying Data Science: Business Case Studies Using SAS, by Gerhard Svolba, shows you the benefits of analytics, how to gain more insight into your data, and how to make better decisions. In eight entertaining and real-world case studies, Svolba combines data science and advanced analytics with business questions, illustrating them with data and SAS code. The case studies range from a variety of fields, including performing headcount survival analysis for employee retention, forecasting the demand for new projects, using Monte Carlo simulation to understand outcome distribution, among other topics. The data science methods covered include Kaplan-Meier estimates, Cox Proportional Hazard Regression, ARIMA models, Poisson regression, imputation of missing values, variable clustering, and much more! Written for business analysts, statisticians, data miners, data scientists, and SAS programmers, Applying Data Science bridges the gap between high-level, business-focused books that skimp on the details and technical books that only show SAS code with no business context.



Machine Learning With Sas Viya


Machine Learning With Sas Viya
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Author : SAS Institute Inc.
language : en
Publisher: SAS Institute
Release Date : 2020-05-29

Machine Learning With Sas Viya written by SAS Institute Inc. and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-29 with Computers categories.


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



Text Analytics With Sas


Text Analytics With Sas
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Author :
language : en
Publisher:
Release Date : 2019-06-14

Text Analytics With Sas written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-14 with categories.


SAS provides many different solutions to investigate and analyze text and operationalize decisioning. Several impressive papers have been written to demonstrate how to use these techniques. We have carefully selected a handful of these from recent Global Forum contributions to introduce you to the topic and let you sample what each has to offer. Also available free as a PDF from sas.com/books.



Big Data Analytics Made Easy


Big Data Analytics Made Easy
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Author : Y. Lakshmi Prasad
language : en
Publisher: Notion Press
Release Date : 2016-12-14

Big Data Analytics Made Easy written by Y. Lakshmi Prasad and has been published by Notion Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-14 with Computers categories.


Big Data Analytics Made Easy is a must-read for everybody as it explains the power of Analytics in a simple and logical way along with an end to end code in R. Even if you are a novice in Big Data Analytics, you will still be able to understand the concepts explained in this book. If you are already working in Analytics and dealing with Big Data, you will still find this book useful, as it covers exhaustive Data Mining Techniques, which are considered to be Advanced topics. It covers Machine Learning concepts and provides in-depth knowledge on unsupervised as well as supervised Learning, which is very important for decision-making. The toughest Data Analytics concepts are made simpler, It features examples from all the domains so that the reader gets connected to the book easily. This book is like a personal trainer that will help you master the Art of Data Science.