Story
Slides
Spotfire Dashboard
Slides SAS Visual Analytics: An Overview
Silver Spotfire Feature Matrix
Silver Spotfire Version Comparison
Research Notes

SAS

Last modified

Story
Slides
Spotfire Dashboard
Slides SAS Visual Analytics: An Overview
Silver Spotfire Feature Matrix
Silver Spotfire Version Comparison
Research Notes

Story
Slides
Spotfire Dashboard
Slides SAS Visual Analytics: An Overview
Silver Spotfire Feature Matrix
Silver Spotfire Version Comparison
Research Notes

Story

OMB Data Visualization Tool Requirements Analysis: SAS

Slides

Background

DRAFT White Paper for OMB Pittsburgh, July 11, 2013.
Start With the End in Mind, Avoid Tool and Turf Wars, and Develop Well-designed Spreadsheets That Can be “Dragged and Dropped” Onto a Tool That Creates Statistics and Visualizations in the Public and Private Clouds.
Focus on Requirements Analysis by First Comparing Magic Quadrant Leaders and Challengers on Common Data Sets.
Spotfire Was Able to Reproduce Birst, Information Builders, Logi Analytics, Microsoft, QlikView, and Tableau Data Visualizations With Dynamically Linked Visualizations.
Broaden This Requirements Analysis to Include More Sample Data Sets and Tools.
SAS Is a Leader in the Gartner Magic Quadrant.

Gartner BI Magic Quadrant: SAS
SAS Analytics Strengths and Cautions Excerpts

SAS's portfolio includes tools in areas such as BI, performance management, data warehousing and data quality; however, unlike most other BI platform vendors, SAS primarily focuses on advanced analytical techniques, such as data mining and predictive modeling, where references acknowledge it as a leader.
The solution-oriented analytic application approach to the market is a differentiator, giving the company the advantage of having a wide variety of cross-functional and vertically specific analytic applications out of the box for a wide variety of industries, including financial services, life sciences, retail, communications and manufacturing.
In 2012, SAS announced Visual Analytics, the new data discovery product that merges dashboard design with diagnostic analytics and the use of predictive models — a possibility not yet available in some of its competitors' tools. Visual Analytics also provides mobile BI capabilities — a gap that, until now, had been resolved through a partnership with MeLLmo Roambi. Moreover, it is the first visible result of a comprehensive initiative to standardize user interfaces and to better integrate the product portfolio — an area where SAS scores lower than most other vendors in the Magic Quadrant survey. For SAS, it's also a key instrument to reach beyond analytics experts to a more mainstream audience, thereby preventing competitors' data discovery tools from doing so on its customer base.
References continue to report that SAS is very difficult to implement and use — it was the No. 3 vendor in both categories.
SAS's dominance in predictive analytics and statistics continues to be challenged on many fronts. IBM is still the main challenger with SPSS and other analytic assets, but wide support of open-source R by large competitors, such as Oracle, SAP and other smaller vendors, will be the most serious threat in the long term. R is challenging SAS for the title of standard coding language for analytics, and is increasingly considered a credible alternative by professionals in the market, eroding SAS's dominance in the analytics community. Other vendors, such as Kxen (not included in this Magic Quadrant), Prognoz, Alteryx or Tibco, are additional sources of competition as more customers adopt analytics.
Despite SAS's success and awareness as a leader in the predictive analytics space, the company is still challenged to make it onto BI platform shortlist evaluations when predictive analytics is not a primary business requirement.

Note: Bolding by the author to highlight key points.
Source: http://www.gartner.com/technology/re...t=130206&st=sb

Some Conclusions and Recommendations

Semantic Community Was Able to Import SAS Files Into Spotfire and Export CSV Files From SAS Visual Analytics and Import Them Into Spotfire.
Spotfire Provides Similar Features To SAS Visual Analytics, But the Author Finds Spotfire Much Easier to Use.
MindTouch and Spotfire Are More Versatile Than SAS Visual Analytics For Mashups.
Semantic Community Will Continue to Use The Gartner BI Magic Quadrant Leader Tools and Their Sample Data Sets and to Recreate Visualizations and Dashboards.

Slides

Slide 1 OMB Data Visualization Tool Requirements Analysis: SAS

http://semanticommunity.info/
http://breakinggov.com/author/brand-niemann/
http://semanticommunity.info/Data_Science/Free_Data_Visualization_and_Analysis_Tools/SAS

Slide 2 Background

Slide 10 SAS Visual Analytics: An Overview of Powerful Discovery, Analysis and Reporting

http://www.sas.com/software/visual-a...t-Guide-v3.pdf

Slide 11 SAS Visual Analytics: Knowledge Base

http://semanticommunity.info/Data_Science/Free_Data_Visualization_and_Analysis_Tools/SAS

Slide 12 Silver Spotfire: Feature Matrix

https://silverspotfire.tibco.com/us/...feature-matrix

Slide 13 SAS Providers for OLE DB: Download

http://support.sas.com/demosdownload...0343&jmpflag=N

Slide 14 Silver Spotfire: Version Comparison 1

https://silverspotfire.tibco.com/us/...ion-comparison

Slide 15 Silver Spotfire: Version Comparison 2

https://silverspotfire.tibco.com/us/...ion-comparison

Slide 16 SAS Visual Analytics Data Sets: Spotfire

Web Player

Slide 17 SAS Example Data Sets: Spotfire

Web Player

Slide 18 Some Conclusions and Recommendations

Spotfire Dashboard

For Internet Explorer Users and Those Wanting Full Screen Display Use: Web Player Get Spotfire for iPad App

Slides SAS Visual Analytics: An Overview

Slides

Slide 1 SAS Visual Analytics: An Overview of Powerful Discovery, Analysis and Reporting

Slide 2 Welcome to SAS Visual Analytics

http://www.sas.com/technologies/bi/v...analytics.html

Slide 3 Content

Slide 4 Overview of The Data

Slide 5 Getting Started In SAS Visual Analytics - The Essentials

Slide 6 Bar Charts - The Basics

Slide 7 Bard Chart - Add a Hierarchy

Slide 8 Using a Hierarchy

Slide 9 Exploring a Heirarchy

Slide 10 Creating a Hierarchy

Slide 11 Filters

Slide 12 Filters - Basic

Slide 13 Filters - Select and Include

Slide 14 Filters - Advanced

Slide 15 Calculations

Slide 16 Calculations - Creating

Slide 17 Calculations - Editing

Slide 18 Geographies

Slide19 Analyzing Geographies 1

Slide 20 Analyzing Geographies 2

Slide 21 Refining Geographies

Slide 22 Crosstab - Getting Started 1

Slide 23 Crosstab - Getting Started 2

Slide 24 Crosstab -Adding Depth

Slide 25 Crosstab - Drill Down with Hierarchies

Slide 26 Crosstab - Creating Totals

Slide 27 Forecast - Getting Started

Slide 28 Forecast Product Sale & Product Cost of Sale

Slide 29 Forecast Created

Slide 30 Forecast Filters

Slide 31 Forecasting Properties

Slide 32 Exporting and Using the Forecast Data

Slide 33 Treemaps - Getting Started 1

Slide 34 Treemaps - Getting Started 2

Slide 35 Exploring Treemaps

Slide 36 Treemaps - More Exploration

Slide 37 Heat Maps - Getting Started 1

Slide 38 Heat Maps - Getting Started 2

Slide 39 Heat Maps - Another Perspective

Slide 40 Heat Maps - Drilling Deeper

Slide 41 Heat Maps - Identifying Problem Areas 1

Slide 42 Heat Maps - Identifying Problem Areas 2

Slide 43 Correlations

Slide 44 Correlation Matrix

Slide 45 Correlation Regression

Slide 46 Correlation with Gross Margin

Slide 47 Correlations - Investigating

Slide 48 Satisfied and Profitable Customers...Buy Which Product?

Slide 49 Gross Margin Ratio - Star Products

Slide 50 Box Plots

Slide 51 Box Plots - Using Them

Slide 52 Box Plots - Refinement

Slide 53 Bubble Plots - Getting Started 1

Slide 54 Bubble Plots - Getting Started 2

Slide 55 Bubble Plots - Getting Started 3

Slide 56 Bubble Plots - Exploring

Slide 57 Bubble Plots - Refining

Slide 58 Bubble Plots - Time Animation

Slide 59 Reporting in SAS Visual Analytics - Getting Started

Slide 60 Reporting in SAS Visual Analytics - The Home Page

Slide 61Reporting in SAS Visual Analytics - Open Sample Report

Slide 62 Reporting in SAS Visual Analytics - The Essentials

Slide 63 Reporting in SAS Visual Analytics - Creating a New Section

Slide 64 Reporting in SAS Visual Analytics - Editing a New Section

Slide 65 Reporting in SAS Visual Analytics - Adding a Pie Chart

Slide 66 Reporting in SAS Visual Analytics - Adding a Line Chart 1

Slide 67 Reporting in SAS Visual Analytics - Adding a Line Chart 2

Slide 68 Reporting in SAS Visual Analytics - Adding a Treemap

Slide 69 Reporting in SAS Visual Analytics - Creating Interaction

Slide 70 Reporting in SAS Visual Analytics - Working with the Report

Slide 71 Reporting in SAS Visual Analytics - Finalizing the Report

Slide 72 Reporting in SAS Visual Analytics - View Reports

Slide 73 Explore!

Slide 74 Insight Toys Company - Data Dictionary 1

Slide 75 Insight Toys Company - Data Dictionary 2

Slide 76 Insight Toys Company - Data Dictionary 3

Slide 77 Insight Toys Company - Data Dictionary 4

Slide 78 Insight Toys Company - Data Dictionary 5

Silver Spotfire Feature Matrix

Source: https://silverspotfire.tibco.com/us/get-spotfire/silver-spotfire-feature-matrix

Detailed feature list

Versions	Personal	Personal Plus	Publisher	Analyst
Trial	One year	One month	One month	One month
Monthly Subscription	na	na	$99	$399
Annual Subscription	na	$99	$1000	$4500
Web Sharing	Personal	Personal Plus	Publisher	Analyst
Apple® iPad® Compatibility	●	●	●	●
Public Sharing	●	●	●	●
Invitation-Only Web Sharing		●	●	●
Public Content: Max Concurrent Web Viewers	10	20	50	50
Private Content: Max Named Web Viewers	0	2	5	5
Offline Data	∞	∞	∞	∞
Online Storage (MB)	50MB	100MB	250MB	500MB
Online Storage (rows)	~10k	~100k	~1M	~5M
Data Access	Personal	Personal Plus	Publisher	Analyst
Replace Data Tool	●	●	●	●
Load from Microsoft® Excel®, csv, txt	●	●	●	●
Load SAS files (Requires installation of SAS Providers for OLE DB)	●	●	●	●
Load from Microsoft Access®	●	●	●	●
Load from Microsoft SQL Server® databases			●	●
Load from Microsoft SQL Server Analysis Services® databases			●	●
Load from OLE DB compatible data sources			●	●
Load from ODBC compatible data sources			●	●
Load from Oracle® databases			●	●
Load from Teradata® databases			●	●
Application Building Tools	Personal	Personal Plus	Publisher	Analyst
Create Custom Hierarchy	●	●	●	●
Capture Private and Public Bookmarks	●	●	●	●
Action Links			●	●
Multiple Data Tables in One Application			●	●
Data Transformation Tools			●	●
Merge Datasets			●	●
Insert Calculated Column			●	●
Text Area Controls to Switch Axes and Variables			●	●
Tag Data			●	●
Interactive Visualizations	Personal	Personal Plus	Publisher	Analyst
Visual Joining of Multiple Data Sources	●	●	●	●
Embedded Geographic Shape Files	●	●	●	●
Table	●	●	●	●
Cross Table	●	●	●	●
Bar Chart	●	●	●	●
Line Chart	●	●	●	●
Bar & Line Chart	●	●	●	●
Pie Chart	●	●	●	●
Text Area	●	●	●	●
Map Chart	●	●	●	●
Scatter Plot			●	●
3D Scatter Plot				●
Treemap			●	●
Graphical Table			●	●
Box Plot				●
Heat Map				●
Parallel Coordinates Plot				●
Summary Table				●
Analytic Options and Tools	Personal	Personal Plus	Publisher	Analyst
Advanced Calculations	●	●	●	●
Conditional Coloring Rules	●	●	●	●
Reference Lines in Plots	●	●	●	●
Trellis mode	●	●	●	●
Capture Private Bookmarks	●	●	●	●
Number Formatting	●	●	●	●
Multi-Y Scaling	●	●	●	●
Business Aggregations	●	●	●	●
Custom Expressions			●	●
Analytic Aggregations				●
Lists				●
Curve Drawing				●
Curve Fitting				●
Line Similarity Tool				●
K-Means Clustering Tool				●
Data Relationships Tool				●
Hierarchical Clustering Tool				●
Predictive Modeling				●
Insert Predicted Columns				●
Miscellaneous	Personal	Personal Plus	Publisher	Analyst
Allow Data Export by Web User	●	●	●	●
Print	●	●	●	●
Export Data	●	●	●	●
Export to Powerpoint			●	●
Export to PDF			●	●

TIBCO Silver™ Spotfire® client is not for use with other TIBCO Spotfire® deployments. The client may only to be used for connecting to a TIBCO Silver™ Spotfire® server (https://silverspotfire.tibco.com)

Regarding licensing and units, TIBCO Silver™ Spotfire® products are delivered on a Term License basis, client use is per Named User, and web sharing limitations are defined using Concurrent Users for public content and Named Users for private content. Named Client User means a Named User who uses the downloadable and locally installable TIBCO Silver™ Spotfire® client software. Named Web User means a Named User who uses a TIBCO Spotfire® file through a web browser. More details on TIBCO product definitions are available at:http://www.tibco.com/software/productdefinitions.jsp

Questions? Contact mds@tibco.com

Silver Spotfire Version Comparison

Source: https://silverspotfire.tibco.com/us/silver-spotfire-version-comparison

Silver Spotfire Version Comparison

* Bold text indicates key upgrade criteria.

Type	Personal	Personal Plus	Publisher	Analyst
Price / Term	Free for one year	$99 /year	$99 /month $1000 /year	$399 /month $4500/year
Maximum number of Concurrent read-only web users of your public content	10	20	50	50
Maximum number of Named read-only web users to whom you can grant access to your private web content	0	2	5	5
Online Storage for Web Content	50MB (~10k rows)	100MB (~100k rows)	250MB (~1M rows)	500MB (~5M rows)
Web Application Sharing	Public only	Public *Password protected* *Invitation-only access*	Public Password protected Invitation-only access	Public Password protected Invitation-only access
Data Access	MS Excel, MS Access	MS Excel, MS Access	Microsoft Excel and Access *Direct access to databases via OLE DB or ODBC*	Microsoft Excel and Access Direct access to databases via OLE DB or ODBC Access to Microsoft SQL Server, Oracle MySQL, PostgreSQL, Microsoft SQL Server Analysis Services, Oracle and Teradata
Productivity	Replace data tool	Replace data tool	Replace data tool *Multiple datasets in one Spotfire file* *Reshape and merge datasets* *Calculated columns* *Custom expressions*	Replace data tool Multiple datasets in one Spotfire file Reshape and merge datasets Calculated columns Custom expressions
Application Building	Capture Bookmarks	Capture Bookmarks	Capture Bookmarks Action Links	Capture Bookmarks *Action Links*
Visuals	Dashboard visuals (bar, line, pie, map, cross table)	Dashboard visuals (bar, line, pie, map, cross table)	Dashboard visuals *Additional visuals: Scatter Plot, Treemap, Graphical Table)*	Dashboard visuals 3D Scatterplot Additional Visuals *Advanced visuals to manage Big Data: (Heatmap, Parallel Coordinate Plot, Box Plot)*
Analytics	Filter & Drill	Filter & Drill	Filter & Drill	Filter & Drill *Curve fitting, advanced aggregations, and analytic tools for correlation, similarity, and clustering* *Predictive Modeling and ability to insert predicted columns*
Collaboration	Capture Private and Public Bookmarks	Capture Private and Public Bookmarks	Capture Private and Public Bookmarks *Tags* *Lists*	Capture Private and Public Bookmarks Tags Lists

Regarding licensing and units, TIBCO Silver™ Spotfire® products are delivered on a Term License basis, client use is per Named User, and web sharing limitations are defined using Concurrent Users for public content and Named Users for private content. Named Client User means a Named User who uses the downloadable and locally installable TIBCO Silver™ Spotfire® client software. Named Web User means a Named User who uses a TIBCO Spotfire® file through a web browser. More details on TIBCO product definitions are available at: http://www.tibco.com/software/productdefinitions.jsp

Questions? Contact mds@tibco.com

Research Notes

Source: http://www.gartner.com/technology/reprints.do?id=1-1DYKLUR&ct=130206&st=sb

Gartner BI Magic Quadrant: SAS Strenghts and Cautions Excerpts

SAS's portfolio includes tools in areas such as BI, performance management, data warehousing and data quality; however, unlike most other BI platform vendors, SAS primarily focuses on advanced analytical techniques, such as data mining and predictive modeling, where references acknowledge it as a leader.

The solution-oriented analytic application approach to the market is a differentiator, giving the company the advantage of having a wide variety of cross-functional and vertically specific analytic applications out of the box for a wide variety of industries, including financial services, life sciences, retail, communications and manufacturing.

In 2012, SAS announced Visual Analytics, the new data discovery product that merges dashboard design with diagnostic analytics and the use of predictive models — a possibility not yet available in some of its competitors' tools. Visual Analytics also provides mobile BI capabilities — a gap that, until now, had been resolved through a partnership with MeLLmo Roambi. Moreover, it is the first visible result of a comprehensive initiative to standardize user interfaces and to better integrate the product portfolio — an area where SAS scores lower than most other vendors in the Magic Quadrant survey. For SAS, it's also a key instrument to reach beyond analytics experts to a more mainstream audience, thereby preventing competitors' data discovery tools from doing so on its customer base.

References continue to report that SAS is very difficult to implement and use — it was the No. 3 vendor in both categories.

SAS's dominance in predictive analytics and statistics continues to be challenged on many fronts. IBM is still the main challenger with SPSS and other analytic assets, but wide support of open-source R by large competitors, such as Oracle, SAP and other smaller vendors, will be the most serious threat in the long term. R is challenging SAS for the title of standard coding language for analytics, and is increasingly considered a credible alternative by professionals in the market, eroding SAS's dominance in the analytics community. Other vendors, such as Kxen (not included in this Magic Quadrant), Prognoz, Alteryx or Tibco, are additional sources of competition as more customers adopt analytics.

Despite SAS's success and awareness as a leader in the predictive analytics space, the company is still challenged to make it onto BI platform shortlist evaluations when predictive analytics is not a primary business requirement.

Table of contents

SAS

Table of contents

Story

Slides

Slide 1 OMB Data Visualization Tool Requirements Analysis: SAS

Slide 2 Background

Slide 3 Gartner BI Magic Quadrant: SAS

Slide 4 SAS: Home Page

Slide 5 SAS: Visual Analytics

Slide 6 SAS: Registration

Slide 7 SAS: Full Demo

Slide 8 SAS: Visual Analytics Client

Slide 9 SAS: Data Dictionary Spreadsheet

Slide 10 SAS Visual Analytics: An Overview of Powerful Discovery, Analysis and Reporting

Slide 11 SAS Visual Analytics: Knowledge Base

Slide 12 Silver Spotfire: Feature Matrix

Slide 13 SAS Providers for OLE DB: Download

Slide 14 Silver Spotfire: Version Comparison 1

Slide 15 Silver Spotfire: Version Comparison 2

Slide 16 SAS Visual Analytics Data Sets: Spotfire

Slide 17 SAS Example Data Sets: Spotfire

Slide 18 Some Conclusions and Recommendations

Spotfire Dashboard

Slides SAS Visual Analytics: An Overview

Slide 1 SAS Visual Analytics: An Overview of Powerful Discovery, Analysis and Reporting

Slide 2 Welcome to SAS Visual Analytics

Slide 3 Content

Slide 4 Overview of The Data

Slide 5 Getting Started In SAS Visual Analytics - The Essentials

Slide 6 Bar Charts - The Basics

Slide 7 Bard Chart - Add a Hierarchy

Slide 8 Using a Hierarchy

Slide 9 Exploring a Heirarchy

Slide 10 Creating a Hierarchy

Slide 11 Filters

Slide 12 Filters - Basic

Slide 13 Filters - Select and Include

Slide 14 Filters - Advanced

Slide 15 Calculations

Slide 16 Calculations - Creating

Slide 17 Calculations - Editing

Slide 18 Geographies

Slide19 Analyzing Geographies 1

Slide 20 Analyzing Geographies 2

Slide 21 Refining Geographies

Slide 22 Crosstab - Getting Started 1

Slide 23 Crosstab - Getting Started 2

Slide 24 Crosstab -Adding Depth

Slide 25 Crosstab - Drill Down with Hierarchies

Slide 26 Crosstab - Creating Totals

Slide 27 Forecast - Getting Started

Slide 28 Forecast Product Sale & Product Cost of Sale

Slide 29 Forecast Created

Slide 30 Forecast Filters

Slide 31 Forecasting Properties

Slide 32 Exporting and Using the Forecast Data

Slide 33 Treemaps - Getting Started 1

Slide 34 Treemaps - Getting Started 2

Slide 35 Exploring Treemaps

Slide 36 Treemaps - More Exploration

Slide 37 Heat Maps - Getting Started 1

Slide 38 Heat Maps - Getting Started 2

Slide 39 Heat Maps - Another Perspective

Slide 40 Heat Maps - Drilling Deeper

Slide 41 Heat Maps - Identifying Problem Areas 1

Slide 42 Heat Maps - Identifying Problem Areas 2

Slide 43 Correlations

Slide 44 Correlation Matrix

Slide 45 Correlation Regression

Slide 46 Correlation with Gross Margin

Slide 47 Correlations - Investigating

Slide 48 Satisfied and Profitable Customers...Buy Which Product?

Slide 49 Gross Margin Ratio - Star Products

Slide 50 Box Plots

Slide 51 Box Plots - Using Them

Slide 52 Box Plots - Refinement

Slide 53 Bubble Plots - Getting Started 1

Slide 54 Bubble Plots - Getting Started 2

Slide 55 Bubble Plots - Getting Started 3