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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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Summary


You were introduced to two additional programming languages included in BASE SAS, the DS2 language and the FedSQL language.

You learned how DS2 is similar and different from the data step and learned that the DS2 language is an oop language. In addition, you were given an overview of DS2 methods and packages.

We covered variable scope as it pertains to an oop language such as DS2. You learned how to use the DS2 procedure and executed several hands-on exercises to learn some of the basics of writing DS2 programs.

Furthermore, you learned through example how to use the FEDSQL procedure to execute FedSQL programs from SAS Studio as well as FedSQL with DS2.

In the next chapter, you will be exposed to the different types of architectures that are part of the SAS platform and will find out how the platform is engineered to enable users to perform big data analytics with SAS.

 

 

 

 

 

 

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