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OMB Data Visualization Tool Requirements Analysis: SAS Dr. Brand Niemann Director and Senior Data Scientist Semantic Community

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Presentation on theme: "OMB Data Visualization Tool Requirements Analysis: SAS Dr. Brand Niemann Director and Senior Data Scientist Semantic Community"— Presentation transcript:

1 OMB Data Visualization Tool Requirements Analysis: SAS Dr. Brand Niemann Director and Senior Data Scientist Semantic Community http://semanticommunity.info/ AOL Government Blogger http://breakinggov.com/author/brand-niemann/ July 26, 2013 http://semanticommunity.info/Data_Science/Free_Data_Visualization_and_Analysis_Tools/SAS 1

2 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. 2

3 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/reprints.do?id=1-1DYKLUR&ct=130206&st=sbhttp://www.gartner.com/technology/reprints.do?id=1-1DYKLUR&ct=130206&st=sb 3

4 SAS: Home Page 4 http://www.sas.com/

5 SAS: Visual Analytics 5 http://www.sas.com/software/visual-analytics/demos/all-demos.html

6 SAS: Registration 6 http://www.sas.com/en_us/offers/13q2/va-try-before-you-buy/register.html

7 SAS: Full Demo 7 http://www.sas.com/software/visual-analytics/demos/full-access.html *This demo uses a predefined data set. Reports will not save between sessions. To try SAS Visual Analytics with your own data, please contact a SAS sales representative. Requested and Searched for: HPS.INSIGHT_TOY2_DEMO Total Rows: 3,597,272 Returned Rows: 3,597,272 Columns Shown: 46 of 58 Filtered: False

8 SAS: Visual Analytics Client 8 http://vatry.ondemand.sas.com/SASVisualAnalyticsExplorer/VisualAnalyticsExplorer/VisualAnalyticsExplorerApp.jsp#

9 SAS: Data Dictionary Spreadsheet 9 http://semanticommunity.info/@api/deki/files/25244/SAS.xlsx HPS.INSIGHT_TOY2_DEMO Total Rows: 3,597,272 Returned Rows: 3,597,272 Columns Shown: 43 of 58

10 SAS Visual Analytics: An Overview of Powerful Discovery, Analysis and Reporting 10 http://www.sas.com/software/visual-analytics/demos/explore/SAS-Visual-Analytics-Quickstart-Guide-v3.pdf

11 SAS Visual Analytics: Knowledge Base 11 http://semanticommunity.info/Data_Science/Free_Data_Visualization_and_Analysis_Tools/SAS

12 Silver Spotfire: Feature Matrix 12 https://silverspotfire.tibco.com/us/get-spotfire/silver-spotfire-feature-matrix Need this to use SAS data sets.

13 SAS Providers for OLE DB: Download 13 http://support.sas.com/demosdownloads/downarea_t1.jsp?productID=110343&jmpflag=N

14 Silver Spotfire: Version Comparison 1 14 https://silverspotfire.tibco.com/us/silver-spotfire-version-comparison Blue Text indicates key upgrade criteria.

15 Silver Spotfire: Version Comparison 2 15 https://silverspotfire.tibco.com/us/silver-spotfire-version-comparison

16 SAS Visual Analytics Data Sets: Spotfire 16 https://silverspotfire.tibco.com/us/library#/users/bniemann/Public?SAS-Spotfire.dxp

17 SAS Example Data Sets: Spotfire 17 https://silverspotfire.tibco.com/us/library#/users/bniemann/Public?SAS-Spotfire.dxp

18 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. 18


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