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 (c). 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.
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