Big Data Analytics with SAS: Get actionable insights from your Big Data using the power of SAS
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Packt Publishing
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FYI: Big Data Analytics with SAS was named "One of the best Data Science books of all time" and "One of the best new Data Science books"by BookAuthority.
SAS' tag line is The Power to Know, But what makes SAS so powerful? Ask SAS users and they'll tell you -- it's because SAS allows them to answer questions which previously could not be answered. How does SAS do this? SAS built a 4th generation programming language which makes it easier for users to prepare data for analytics, perform analytics, and then deploy the results of analytics into production systems. As you might imagine, it's not possible to write one book that can provide a programmer with a deep and broad dive into everything that SAS offers -- especially when you start considering some of the solutions SAS has built based on customer's feedback to address specific industry issues (like anti-money laundering, predictive asset maintenance, or utility load forecasting). However, Big Data Analytics with SAS gives new programmers one of the best overviews of the power that lies within the foundation of the SAS programming language, along with providing experienced programmers who don't know SAS a guide that will allow them to quickly learn it. The book also explains how the SAS platform is designed to allow the analysis of big data analytics to happen at scale. Don't worry about having a license of SAS because readers can make use of the free SAS University Edition and use SAS Studio and/or an Ipython Juypter Notebook as the interfaces to program in SAS.
I hope you'll check it out!
SAS' tag line is The Power to Know, But what makes SAS so powerful? Ask SAS users and they'll tell you -- it's because SAS allows them to answer questions which previously could not be answered. How does SAS do this? SAS built a 4th generation programming language which makes it easier for users to prepare data for analytics, perform analytics, and then deploy the results of analytics into production systems. As you might imagine, it's not possible to write one book that can provide a programmer with a deep and broad dive into everything that SAS offers -- especially when you start considering some of the solutions SAS has built based on customer's feedback to address specific industry issues (like anti-money laundering, predictive asset maintenance, or utility load forecasting). However, Big Data Analytics with SAS gives new programmers one of the best overviews of the power that lies within the foundation of the SAS programming language, along with providing experienced programmers who don't know SAS a guide that will allow them to quickly learn it. The book also explains how the SAS platform is designed to allow the analysis of big data analytics to happen at scale. Don't worry about having a license of SAS because readers can make use of the free SAS University Edition and use SAS Studio and/or an Ipython Juypter Notebook as the interfaces to program in SAS.
I hope you'll check it out!
About the Author
David Pope has worked for SAS for over 27 years in a variety of departments, including research and development (R&D), information technology (IT), SAS Solutions on Demand (SSOD), and sales and marketing. He graduated from North Carolina State University with a bachelor's of science in industrial engineering and a certificate in computer programming. He started his career with SAS, testing and writing code for the SAS system in R&D using C, Java, and of course SAS programming languages.
David has worked in both the United States and Europe in this capacity. Then he moved into IT within SAS to help support running it as a business, using SAS and other technologies such as JavaScript, HTML, and Unix/Linux scripting languages. He spent 4 years working as a consultant with SAS customers in SSOD prior to moving into presales support, where he worked across all industries as an analytics and SAS architecture expert. David moved into presales management to build out a team of data scientists and technical architects who support opportunities in the US energy industry, electric utilities, and oil and gas companies. He currently holds 11 patents for SAS and is an active blogger under the SASVoices corporate blog. He is a life-long learner who enjoys teaching and empowering people to solve business problems.
David has worked in both the United States and Europe in this capacity. Then he moved into IT within SAS to help support running it as a business, using SAS and other technologies such as JavaScript, HTML, and Unix/Linux scripting languages. He spent 4 years working as a consultant with SAS customers in SSOD prior to moving into presales support, where he worked across all industries as an analytics and SAS architecture expert. David moved into presales management to build out a team of data scientists and technical architects who support opportunities in the US energy industry, electric utilities, and oil and gas companies. He currently holds 11 patents for SAS and is an active blogger under the SASVoices corporate blog. He is a life-long learner who enjoys teaching and empowering people to solve business problems.
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