Information Visualization 2013


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Information Visualization is becoming an increasingly important strategy to provide dashboard consumers insights into their information deluge. It is important for practitioners to learn how to design dashboards in the most effective ways.

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  • Very cool tag cloud of BI/Information visualization termsWhen you look at a tag cloud, what is it communicating?
  • Moving away from HiPPO—the highest-paidperson’sopinion to data-driven analytics based decision-makingIt used to be that dashboards were primarily for the EIM (Executive rooms) but now are being pushed to all levels of a company
  • Moving to self-serve, enabling people to measure themselves, and enabling or driving data-driven decisions
  • Collapsing the distance between the circles is an important objective for companies
  • Transparency, decision-making, corrective actions before emergency / crisis
  • As IT/Data/Business practitioners we need to maximize the value for the dashboard consumers
  • Source of image:
  • EIM (Executive Information Management)Quantitative : example is forecast, metrics, KPI, SLANon-quantitative: example is top X customers, My Sales Funnel, Today’s activities
  • We can cover the examples in the discussion part of the presentation.
  • Audience: Executive, Analysts, end usersGive the appropriate amount of filters, drop-downs, etc.
  • Information Visualization 2013

    1. 1. A short presentation on BI visual analysis. by Paul Hansford, MS Senior Consultant Simplesoft Solutions, Inc.8/23/2013 – TechnologyFirst BI SIG
    2. 2. Source:
    3. 3. • Introduction • Terms to think about • Types of visualization/levels of maturity • 13 Don’t’s and some do’s • Resources • Discussion Data Rich, Information Poor (D.R.I.P.)
    4. 4. Get The Information In Front Of The Right Group
    5. 5. Challenges • Saving time from manual report building processes to near real- time dashboards (business intelligence) • Saving labor (IT) from manual report building to dashboards • Moving from data collection to insights (analyze) • Moving from insights to decisions (decide) • Moving from decisions to actions (act) Bottom line: Insight deficit, trustworthy data, time delays, decision-making, and speed in taking action. So, how do we build dashboards to enable the above?
    6. 6. Collect Analyze Decide Act
    7. 7. Collect Analyze Decide Act Review Collaborate Collaborate Workflow Collaborate
    8. 8. LOB System TechnologyStack Dashboards Interactive filtering Improved Decision Outcome You are here! Information Visualization
    9. 9. • Optimize business processes • Greater visibility into the business • Identify potential training opportunities • Enable better decision-making • Measure and record performance, KPI’s and SLA’s What other outcomes are we looking for?
    10. 10. Effective execution of key process Intelligent resource deployment and utilization MEASURABLE RESULTS Bottom line: More value
    11. 11. Get more work done with fewer resources in the office, at home, or on the road. Improve Business Insight Reduce Costs and Risks Gain better insight into business drivers to make more informed decisions about improving competitive position. Find customers more cost-effectively, close deals faster, and gain better insight into customer preferences to improve customer service, satisfaction, and loyalty. Reduce cost and complexity by deploying high-value, easy-to-manage technology products. Top Priorities Save Time and Get Organized Find and Retain Customers
    12. 12. Source:
    13. 13. Purpose of Dashboard “A dashboard is a visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance.” - Visual information - Achieve objectives - Single screen - Quickly monitored Source: Intelligent Enterprise, March 2004, “Dashboard Confusion.” , Stephen Few “a picture is worth a thousand words”
    14. 14. • Visualization • Glyph icon • Dashboards • KPI • Scorecard • Metrics • Chart junk • SLA • Gauge • Filter • UX • ERSI • BAM • EPM Homework assignments!
    15. 15. Role • Strategic • Tactical (Analytical) • Operational Types of Data • Quantitative • Non-quantitative Can you give me some quick examples?
    16. 16. Thirteen Don’ts from author Stephen Few • Exceeding the boundaries of a single screen • Supplying inadequate context for the data • Displaying excessive detail or precision • Choosing inappropriate display media • Introducing meaningless variety • Using poorly designed display media • Encoding quantitative data inaccurately
    17. 17. • Arranging the data poorly • Highlighting important data ineffectively or not at all • Cluttering the display with useless decoration • Misusing or overusing color • Designing an unattractive visual display • Consider your audience • Simplify, simplify, simplify! • Use MAD model (Monitor, Analyze, Drill-down) principles
    18. 18. Books: • Information Dashboard Design, Stephen Few (other books as well) • Performance Dashboards, Wayne Eckerson • Effective Dashboard Design, Gail La Grouw • Beautiful Evidence, Edward R. Tufte • Information Visualization: Perception for Design, Colin Ware • Business Dashboards: A Visual Catalog for Design and Deployment, Nils H. Rasmussen, Manish Bansal Any books by Tom Davenport or Vivek Ranadive Websites:
    19. 19. Magazines:, INFORMS, IBM Data magazine, Teradata magazine online Certifications: CAP (Certified Analytics Professional) TDWI’s CBIP (Certified Business Intelligence Professional) Numerous vendor certifications
    20. 20. Examples Good, the bad, and the ugly Information Visualization in Motion