An Introduction to SAS Visual Analytics

Tricia Aanderud, Rob Collum, Ryan Kumpfmiller

Description

When it comes to business intelligence and analytical capabilities, SAS Visual Analytics is the premier solution for data discovery, visualization, and reporting. An Introduction to SAS Visual Analytics will show you how to make sense of your complex data with the goal of leading you to smarter, data-driven decisions without having to write a single line of code – unless you want to! You will be able to use SAS Visual Analytics to access, prepare, and present your data to anyone anywhere in the world.

SAS Visual Analytics automatically highlights key relationships, outliers, clusters, trends and more. These abilities will guide you to critical insights that inspire action from your data. With this book, you will become proficient using SAS Visual Analytics to present data and results in customizable, robust visualizations, as well as guided analyses through auto-charting. With interactive dashboards, charts, and reports, you will create visualizations which convey clear and actionable insights for any size and type of data.

This book largely focuses on the version of SAS Visual Analytics on SAS 9.4, although it is available on both 9.4 and SAS Viya platforms. Each version is considered the latest release, with subsequent releases planned to continue on each platform; hence, the Viya version works similarly to the 9.4 version and will look familiar. This book covers new features of each and important differences between the two.

With this book, you will learn how to:

Build your first report using the SAS Visual Analytics Designer

• Prepare a dashboard and determine the best layout
  
• Effectively use geo-spatial objects to add location analytics to reports
  
• Understand and use the elements of data visualizations
  
• Prepare and load your data with the SAS Visual Analytics Data Builder
  
• Analyze data with a variety of options, including forecasting, word clouds, heat maps, correlation matrix, and more
  
• Understand administration activities to keep SAS Visual Analytics humming along
  
• Optimize your environment for considerations such as scalability, availability, and efficiency between components of your SAS software deployment and data providers
  

Sujets

• Big data
• Data visualization
• Business intelligence

Informations

• Publié par: SAS Institute
• Date de parution: 21 mars 2017
• Nombre de lectures: 0
• EAN13: 9781635260427
• Langue: English
• Poids de l'ouvrage: 22 Mo

Extrait

An Introduction to SAS Visual Analytics
How to Explore Numbers, Design Reports, and Gain Insight into Your Data
Tricia Aanderud Rob Collum Ryan Kumpfmiller
The correct bibliographic citation for this manual is as follows: Aanderud, Tricia, Rob Collum, and Ryan Kumpfmiller. 2017. An Introduction to SAS Visual Analytics: How to Explore Numbers, Design Reports, and Gain Insight into Your Data . Cary, NC: SAS Institute Inc.
An Introduction to SAS Visual Analytics: How to Explore Numbers, Design Reports, and Gain Insight into Your Data
Copyright 2017, SAS Institute Inc., Cary, NC, USA
ISBN 978-1-62960-291-2 (Hard copy) ISBN 978-1-63526-042-7 (EPUB) ISBN 978-1-63526-043-4 (MOBI) ISBN 978-1-63526-044-1 (PDF)
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contents
about this book
about these authors
acknowledgements
introduction
part one: getting started
chapter one: accessing content
Methods of accessing content
Accessing content with a web browser
Accessing content through the public portal
Accessing content with the mobile bi app
Understanding roles
Accessing SAS Visual Analytics
Transformation of the homepage
Understanding SAS home
Opening a report
Creating a shortcut
Creating a collection or content tile
Using the report viewer
Navigating a report
References
chapter two: building your first report
Accessing the designer
Introducing the designer layout
Building your first report
Adding a data source
Creating new data items
Populating your objects
Improving the data object appearance
Adding data to other objects
Working with data objects
Adding object interactions
Saving the report
Reviewing the report
References
chapter three: building your first dashboard
Dashboard building process
Understanding your customer
Establishing objectives
Tips for more useable dashboards
Building the dashboard
Adding the data objects
Creating the layout
Working with data objects
Linking to another section
Other dashboard enhancements
Adding text boxes
Adding artwork
Embedding a stored process
Summary
References
chapter four: using the data builder
Using the Data Builder
Creating a data query
Opening the Data Builder
Filtering the data
Create a summary data query
Updating the code
Scheduling a query
References
part two: customizing your data visualizations
chapter five: visualizing your data
Elements of an effective data visualization
Your message: know your point
Your audience: know who is listening
Your technique: follow the KISS principle
Line charts
Interpreting the results
Line charts: guidelines
Line charts: tips and tricks
Bar charts
Interpreting the results
Bar charts: guidelines
Bar charts: tips and tricks
Pie and donut charts
Interpreting the results
Pie and donut charts: guidelines
Pie and donut charts: tips and tricks
Treemaps
Interpreting the results
Treemaps: guidelines
Treemaps: tips and tricks
Waterfall charts
Interpreting the results
Waterfall charts: guidelines for use
Waterfall charts: tips and tricks
Gauges
Interpreting results
Gauges: Guidelines
Gauges: tips and tricks
Tip 1: Use display rules
Tip 2: Add a shared rule
Tables and cross tabs
Interpreting the results
Tables and crosstabs: guidelines for use
Tables and crosstabs: tips and tricks
Bubble plots
Interpreting the results
Bubble plots: guidelines
Bubble plots: tips and tricks
References
chapter six: the where of data
Using geospatial data effectively
When location is not part of the data story
When location is the data story
Preparing data for geospatial visualizations
Creating a predefined geographic data item
Creating a predefined geographic data item
Creating a custom geospatial data item
Creating a custom geographic data item
Displaying geospatial objects
Get to the point with geo coordinate data objects
Compare area with geo regional data objects
Show overall trends with bubble plots data objects
Expanding location intelligence
Understanding details about mapping technologies
References
chapter seven: approachable analytics
About the Explorer
Automatic chart feature
Box plots
Interpreting the results
Adding more data items
When to use box plots
Histograms
Changing objects in a visualization
Histogram options
Using a correlation matrix
Calculating a correlation
Understanding the matrix
Interpreting a correlation value
Forecasting
Working with the forecasting option
Using the scenario analysis
Word clouds
Loading social media data
Setting up the word cloud
Scatter plot
Data analysis
Adding categories
Heat map
Data analysis
Using a category
Other tips when using the Explorer
Include and exclude
Moving visualizations to the Designer
References
part three: administration and data loading
chapter eight: loading data
In-memory is different
It s about speed
Understanding the non-distributed deployment
Understanding the distributed deployment
Loading data to LASR from HDFS
Enabling support for SASHDAT files
The exception to the rule
SASHDAT does not require SAS/ACCESS
Loading data to LASR from Base SAS
Loading data to LASR with SAS In-Database technology
Loading data to LASR from a different LASR Analytic Server
Loading data into LASR automatically
SAS Autoload to LASR facility
LASR Reload-on-Start feature
References
chapter nine: LASR administration
Administration overview
Administration tools
SAS Management Console
SAS Visual Analytics Administrator
SAS Environment Manager
SAS Program Code
Other tools
Interesting LASR Administration Tasks
The role of SAS metadata
Defining new LASR Analytic Servers
Defining new LASR libraries
Managing LASR Analytic Servers with code
Working with the Autoloader Facility
Monitoring resources used by LASR
References
chapter ten: performance considerations
LASR performance
Non-Distributed LASR (SMP)
Distributed LASR (MPP)
Load balancing by data distribution
High-volume access to smaller tables
Fast loading of data to distributed LASR Analytic Server
LASR and a remote data provider (asymmetric)
LASR symmetrically co-located with HDFS
LASR co-located with dedicated HDFS and loading data from remote HDFS
References
part four: SAS Visual Analytics 8.1
chapter eleven: introducing the SAS Viya platform
Overview of the SAS Viya platform
Understanding the CAS In-Memory Analytics Server
Introducing massively parallel analytics
Adding persisten