An Introduction to SAS Visual Analytics

Book 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

Table of contents

  1. about this book
  2. about these authors
  3. acknowledgements
  4. introduction
  5. part one: getting started
  6. chapter one: accessing content
  7. Methods of accessing content
    1. Accessing content with a web browser
    2. Accessing content through the public portal
    3. Accessing content with the mobile bi app
  8. Understanding roles
    1. Accessing SAS Visual Analytics
    2. Transformation of the homepage
    3. Understanding SAS home
    4. Opening a report
    5. Creating a shortcut
    6. Creating a collection or content tile
  9. Using the report viewer
    1. Navigating a report
  10. References
  11. chapter two: building your first report
  12. Accessing the designer
  13. Introducing the designer layout
  14. Building your first report
    1. Adding a data source
    2. Creating new data items
    3. Populating your objects
    4. Improving the data object appearance
    5. Adding data to other objects
    6. Working with data objects
    7. Adding object interactions
  15. Saving the report
  16. Reviewing the report
  17. References
  18. chapter three: building your first dashboard
  19. Dashboard building process
    1. Understanding your customer
    2. Establishing objectives
    3. Tips for more useable dashboards
  20. Building the dashboard
    1. Adding the data objects
    2. Creating the layout
    3. Working with data objects
    4. Linking to another section
  21. Other dashboard enhancements
    1. Adding text boxes
    2. Adding artwork
    3. Embedding a stored process
  22. Summary
  23. References
  24. chapter four: using the data builder
  25. Using the Data Builder
    1. Creating a data query
  26. Opening the Data Builder
    1. Filtering the data
    2. Create a summary data query
    3. Updating the code
    4. Scheduling a query
  27. References
  28. part two: customizing your data visualizations
  29. chapter five: visualizing your data
  30. Elements of an effective data visualization
    1. Your message: know your point
    2. Your audience: know who is listening
    3. Your technique: follow the KISS principle
  31. Line charts
    1. Interpreting the results
    2. Line charts: guidelines
    3. Line charts: tips and tricks
  32. Bar charts
    1. Interpreting the results
    2. Bar charts: guidelines
    3. Bar charts: tips and tricks
  33. Pie and donut charts
    1. Interpreting the results
    2. Pie and donut charts: guidelines
    3. Pie and donut charts: tips and tricks
  34. Treemaps
    1. Interpreting the results
    2. Treemaps: guidelines
    3. Treemaps: tips and tricks
  35. Waterfall charts
    1. Interpreting the results
    2. Waterfall charts: guidelines for use
    3. Waterfall charts: tips and tricks
  36. Gauges
    1. Interpreting results
    2. Gauges: Guidelines
    3. Gauges: tips and tricks
    4. Tip 1: Use display rules
    5. Tip 2: Add a shared rule
  37. Tables and cross tabs
    1. Interpreting the results
    2. Tables and crosstabs: guidelines for use
    3. Tables and crosstabs: tips and tricks
  38. Bubble plots
    1. Interpreting the results
    2. Bubble plots: guidelines
    3. Bubble plots: tips and tricks
  39. References
  40. chapter six: the where of data
  41. Using geospatial data effectively
    1. When location is not part of the data story
    2. When location is the data story
  42. Preparing data for geospatial visualizations
    1. Creating a predefined geographic data item
    2. Creating a predefined geographic data item
    3. Creating a custom geospatial data item
    4. Creating a custom geographic data item
  43. Displaying geospatial objects
    1. Get to the point with geo coordinate data objects
    2. Compare area with geo regional data objects
    3. Show overall trends with bubble plots data objects
  44. Expanding location intelligence
  45. Understanding details about mapping technologies
  46. References
  47. chapter seven: approachable analytics
  48. About the Explorer
    1. Automatic chart feature
  49. Box plots
    1. Interpreting the results
    2. Adding more data items
    3. When to use box plots
  50. Histograms
    1. Changing objects in a visualization
    2. Histogram options
  51. Using a correlation matrix
    1. Calculating a correlation
    2. Understanding the matrix
    3. Interpreting a correlation value
  52. Forecasting
    1. Working with the forecasting option
    2. Using the scenario analysis
  53. Word clouds
    1. Loading social media data
    2. Setting up the word cloud
  54. Scatter plot
    1. Data analysis
    2. Adding categories
  55. Heat map
    1. Data analysis
    2. Using a category
    3. Other tips when using the Explorer
    4. Include and exclude
    5. Moving visualizations to the Designer
  56. References
  57. part three: administration and data loading
  58. chapter eight: loading data
  59. In-memory is different
  60. It’s about speed
    1. Understanding the non-distributed deployment
    2. Understanding the distributed deployment
  61. Loading data to LASR from HDFS
    1. Enabling support for SASHDAT files
    2. The exception to the rule
    3. SASHDAT does not require SAS/ACCESS
  62. Loading data to LASR from Base SAS
  63. Loading data to LASR with SAS In-Database technology
  64. Loading data to LASR from a different LASR Analytic Server
  65. Loading data into LASR automatically
    1. SAS Autoload to LASR facility
    2. LASR Reload-on-Start feature
  66. References
  67. chapter nine: LASR administration
  68. Administration overview
  69. Administration tools
    1. SAS Management Console
    2. SAS Visual Analytics Administrator
    3. SAS Environment Manager
    4. SAS Program Code
    5. Other tools
  70. Interesting LASR Administration Tasks
    1. The role of SAS metadata
    2. Defining new LASR Analytic Servers
    3. Defining new LASR libraries
    4. Managing LASR Analytic Servers with code
    5. Working with the Autoloader Facility
    6. Monitoring resources used by LASR
  71. References
  72. chapter ten: performance considerations
  73. LASR performance
    1. Non-Distributed LASR (SMP)
    2. Distributed LASR (MPP)
    3. Load balancing by data distribution
    4. High-volume access to smaller tables
  74. Fast loading of data to distributed LASR Analytic Server
    1. LASR and a remote data provider (asymmetric)
    2. LASR symmetrically co-located with HDFS
    3. LASR co-located with dedicated HDFS and loading data from remote HDFS
  75. References
  76. part four: SAS Visual Analytics 8.1
  77. chapter eleven: introducing the SAS Viya platform
  78. Overview of the SAS Viya platform
  79. Understanding the CAS In-Memory Analytics Server
    1. Introducing massively parallel analytics
    2. Adding persistence
    3. Providing more flexibility
  80. SAS Viya and SAS 9.4 together
  81. Managing the SAS Viya environment
    1. Managing users and groups
    2. Managing data
    3. Managing content
  82. References
  83. chapter twelve: wrangling your data
  84. Introducing a modern user interface
    1. New features
  85. References
  86. chapter thirteen: visualizing and exploring your data
  87. Introducing the new layout
  88. Starting a new report
  89. All-in-one application
  90. Additional features
  91. References
  92. index

Product information

  • Title: An Introduction to SAS Visual Analytics
  • Author(s): Tricia Aanderud, Rob Collum, Ryan Kumpfmiller
  • Release date: March 2017
  • Publisher(s): SAS Institute
  • ISBN: 9781635260427