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Big Data Analytics with SAS
Big Data Analytics with SAS

Big Data Analytics with SAS: Get actionable insights from your Big Data using the power of SAS

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Big Data Analytics with SAS

Chapter 2. Working with Data Using SAS® Software

Data can be stored in many forms and in many systems. In  Chapter 1Setting Up the SAS® Software Environment, the topic of SAS data storage was covered from a SAS-centric view, meaning the options available to a user in storing data in SAS datasets. However, SAS can work and store data in a variety of other forms and formats. One of the most powerful features of SAS lies within the data management capabilities designed to read and, more importantly, write data efficiently from all sorts of storage, including database systems, flat files, spreadsheets, mainframe-based formats, and big data storage platforms such as Hadoop and SAP HANA. SAS developers work in partnership with many other vendors in co-developing SAS ACCESS engines, specifically designed to make reading and writing data from their systems as fast and seamless as possible. As a result, SAS data management solutions are used by many customers as a bridge to consolidate and/or share...

Preparing data for analytics


It is important to understand that preparing data for analytics is different than storing data efficiently in a data warehouse, which focuses on normal reporting / business intelligent type and/or ad hoc queries. Regular database administrators (DBAs) will need to be educated and/or convinced that analytics requires the data to be in a different form in order for the algorithms to process the data. It is especially important for the data to be prepared for analytic processing in order for the actual processing to run in a timely manner. Information Technology (IT) employees play an increasingly important role in helping organizations leverage data and analytics. While it isn't necessary for someone in IT to understand statistics or analytics, it is important for them to support the data scientist in acquiring the proper hardware and software to build an analytics platform that runs efficiently so that the business can best leverage the information locked in their...

Summary


The reader learned that data must be stored in a different format in order for analytics to efficiently run, and that this format differs from how data is typically stored in a database. In addition, the reader learned how to make data using SAS statements, as well as how to bring external data into the SAS environment.

The reader should now understand that a SAS library is a pointer to where data is stored, whether the data is stored as a SAS dataset or in some other data storage format such as a database. The reader wrote and executed their first SAS programs, making use of both data step statements and a few BASE SAS procedures. At this point, the reader should be comfortable with working with the CODE, LOG, RESULTS, and other sections that make up a program section within SAS Studio.

In addition, you were introduced to several specialty SAS procedures or PROCs, which enable a programmer to more easily work with specific external data sources or other computer languages.

In Chapter...

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Key benefits

  • 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

Description

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.

Who is this book 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.

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Nov 23, 2017
Length: 266 pages
Edition : 1st
Language : English
ISBN-13 : 9781788294317
Vendor :
SAS Institute
Category :
Concepts :
Tools :

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Product Details

Publication date : Nov 23, 2017
Length: 266 pages
Edition : 1st
Language : English
ISBN-13 : 9781788294317
Vendor :
SAS Institute
Category :
Concepts :
Tools :

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Table of Contents

8 Chapters
Setting Up the SAS Software Environment Chevron down icon Chevron up icon
Working with Data Using SAS Software Chevron down icon Chevron up icon
Data Preparation Using SAS Data Step and SAS Procedures Chevron down icon Chevron up icon
Analysis with SAS Software Chevron down icon Chevron up icon
Reporting with SAS Software Chevron down icon Chevron up icon
Other Programming Languages in BASE SAS Software Chevron down icon Chevron up icon
SAS Software Engineers the Processing Environment for You Chevron down icon Chevron up icon
Why SAS Programmers Love SAS Chevron down icon Chevron up icon

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Caroline Quinn Jan 27, 2018
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I really enjoyed reading this book by David Pope. David and I worked together at SAS. We were both SAS developers. David was always good at seeing the forest instead of the trees. As a very experienced SAS user (35 years), I found the organization and flow of this book to be excellent.I am retired now but I still use SAS. During my career as a manager of SAS developers, one of the biggest challenges in training employees to program in SAS, is getting them to realize the breadth and depth of the products. SAS has a wonderfully flat learning curve, that programmers new to the language and products resist. If I were still managing young developers, especially ones still in college or recently graduated, this is the perfect book to give them a great overview of the immense diversity of SAS software, along with the history. And for experienced SAS developers, this book is a great summary of the products and capabilities of SAS, that they can use as a reference and reminder of the power that they can exploit as they pursue solutions to business problems.As I said earlier, the flow of the book is a great logical progression from installation, language basic, moving to more and more sophisticated data analytics. I thought the coverage of SAS Studio (which is an excellent training tool and great IDE) was very succinct but thorough. Data prep starting with small data and progressing to big data, along with the many analytic tools in the different single-tiered and multi-tiered environments for data analysis and the strengths of the different architectural environments where SAS functions. I loved Chapter 7 SAS® Software Engineers the Processing Environment for You. Though I have worked with SAS servers and grids, as well as in-memory processing, SMP- and MPP-based computing environments, I thought the chapter presented the technologies very well, and illustrated how well SAS dovetails with other technologies (like Hadoop) and database vendors to take maximum advantage of in-database processing. I also learned a few things I don’t know, like using a Jupyter Notebook to interface with SAS. I am itching to try that out now.One of my biggest takeaways from the book was how SAS has always aggressively advanced and adapted to the fast-changing technological landscape. Again, this is a great book for SAS users to learn and understand the immense power of the products that are using, and also what products may provide additional power to their analytics. It’s also a great resource for someone embarking on a career in SAS analytics. Quoting David “The more a programmer learns about the SAS language, they will discover that typically there is more than one way to accomplish a task or solve a problem using SAS.” The strength of this book is showing you how SAS can contribute to your return on your investment in the software. Investing in this book should accelerate your programming and data analytic skills significantly.
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Stephen S. Walker Sep 11, 2018
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I thought the book did an excellent job of covering the full spectrum of SAS's capabilities in regards to extracting value from data with SAS. The author covers the full lifecycle of data analytics and walks you through all the steps necessary to complete a successful SAS big data project, even touching on analytics centers of excellence, and industry-specific topics (healthcare, gov, financial, energy, and manufacturing). For big data specifically, especially in the technical realm, there is very good information on things like SAS proc sql, SAS proc hadoop , and other value-added topics like DS2 (data step 2), SAS IML, and reporting. This book is a great option for both beginners, as well as more advanced data analytics practitioners.
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Kindle Customer Jan 22, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
My perception of SAS was quite different before reading Big Data Analytics with SAS by David Pope.This book is a kind of an eye opener, what the current SAS platform is and where SAS is heading as a company with more than 40 years in the analytics market. David is really making SAS a more approachable software for an average business user.There are some small typos to be corrected. The general experience with the book is very positive.
Amazon Verified review Amazon
Tamara Jan 28, 2018
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SAS has been in the business of analyzing "big" data for decades, long before the term became popular. In this book, David Pope takes a very friendly, step-by-step approach to using SAS analytics with big data. The book steps you through downloading a free version of SAS to setting up your environment to writing your own code for some serious number crunching and analyzing. If you want to get a good solid taste of what SAS is all about, David is well qualified to walk you down that path.
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Lissa Jun 24, 2018
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This book is one of the best on the big data market. I would recommend this to anyone looking for a job in big data or anyone who just wants to learn more about it.
Amazon Verified review Amazon
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