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Big Data Analytics with SAS

Big Data Analytics with SAS

By : Pope
5 (8)
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Big Data Analytics with SAS

Big Data Analytics with SAS

5 (8)
By: Pope

Overview of this book

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.
Table of Contents (17 chapters)
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Why SAS programmers love SAS


SAS programmers love SAS for many reasons, which sometimes are hard to quantify. For example, a colleague of mine, Lisa Dodson, explains one reason this way.  "Many SAS users will talk about how much they like SAS because it makes it easy for them to work with any data. What does that really mean?  Well, if you dive a bit deeper into this statement, it points to SAS' data access capabilities, which free the end user from having to know what data types from different data sources are".  In other words SAS' access layer auto-magically takes care of translating data types to and from the SAS environment.

This is just one example of the power of SAS' data management capabilities that makes SAS programmers love SAS. The TRANSPOSE procedure, along with the FIRST. and LAST. dataset capabilities, which were covered in Chapter 3Data Preparation Using SAS Data Step and SAS Procedures, are other examples of the data management capabilities built into SAS that make it easier...

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