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Data Visualisation

    Alan Robson
   28th May, 2012
Summary
•   Conceptual Architecture
•   Visualisation Cookbook
•   Tools and Trends
•   Choosing a Tool
Conceptual Architecture
                        Visualisation Layer

                          Connection Layer




                               Extract Transform Load
Data Sources


Web      ERP     CRM

                                                        Data Warehouse
Ops      HR      EPOS
A Few Possible Visualisations




   How do we choose?
What are you trying to show?
•   Summary / Snapshot
•   Analysis / Breakdown
•   Comparison / Benchmarking
•   Relationship / Correlation
•   Distribution / Range
•   Trend / Projection / Pattern
Analysis
Summary                       Comparison
             What are you
            trying to show?

    Trend      Relationship   Distribution
What Kind Of Data?
• Time based
  – Small number of periods
  – Large number of periods
• Non-Time based (Static)
• Number of Variables or Categories
  – Single
  – Dual
  – Multiple
Some Guidelines on Design
• Simplicity
   – Avoid visual clutter
• Consistency
   – Colours
   – Navigation
   – Layout
   – Terminology
• Reporting / Highlighting by Exception
   – Draw user to important / urgent issues
• Is it Intuitive?
Gartner Magic Quadrant
Visualisation Tool Trends
• Self Service
• Mobile
• SaaS / Cloud
Which BI Tool is Right for Us?
• Some Considerations
  – Cost
  – Application System Landscape
  – IT Strategy
  – Future Reporting Requirements
  – Inhouse IT Technical Competencies
  – User Competencies
  – Support Model
  – Functionality
Summary
• Know what you are trying to show, understand
  the data
• Choose the right visualisation
• Keep it Simple, Consistent
• Report Exception – avoid overload
• Consider all aspects when choosing a vendor
Thank You
     Alan Robson
arobson@methys.com
    07775 626130
      Business Intelligence
      Financial Reporting
 Financial Reporting Systems
    BusinessIntelligence
     Energy Solutions
        Web Intelligence
         Mobile Apps
         E-commerce
      Mobile Apps
      Web Development
      E-Commerce
      Energy Intelligence

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Data visualisation

  • 1. Data Visualisation Alan Robson 28th May, 2012
  • 2. Summary • Conceptual Architecture • Visualisation Cookbook • Tools and Trends • Choosing a Tool
  • 3. Conceptual Architecture Visualisation Layer Connection Layer Extract Transform Load Data Sources Web ERP CRM Data Warehouse Ops HR EPOS
  • 4. A Few Possible Visualisations How do we choose?
  • 5. What are you trying to show? • Summary / Snapshot • Analysis / Breakdown • Comparison / Benchmarking • Relationship / Correlation • Distribution / Range • Trend / Projection / Pattern
  • 6. Analysis Summary Comparison What are you trying to show? Trend Relationship Distribution
  • 7. What Kind Of Data? • Time based – Small number of periods – Large number of periods • Non-Time based (Static) • Number of Variables or Categories – Single – Dual – Multiple
  • 8. Some Guidelines on Design • Simplicity – Avoid visual clutter • Consistency – Colours – Navigation – Layout – Terminology • Reporting / Highlighting by Exception – Draw user to important / urgent issues • Is it Intuitive?
  • 10. Visualisation Tool Trends • Self Service • Mobile • SaaS / Cloud
  • 11. Which BI Tool is Right for Us? • Some Considerations – Cost – Application System Landscape – IT Strategy – Future Reporting Requirements – Inhouse IT Technical Competencies – User Competencies – Support Model – Functionality
  • 12. Summary • Know what you are trying to show, understand the data • Choose the right visualisation • Keep it Simple, Consistent • Report Exception – avoid overload • Consider all aspects when choosing a vendor
  • 13. Thank You Alan Robson arobson@methys.com 07775 626130 Business Intelligence Financial Reporting Financial Reporting Systems BusinessIntelligence Energy Solutions Web Intelligence Mobile Apps E-commerce Mobile Apps Web Development E-Commerce Energy Intelligence