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Visual Decision Making

Visual Decision Making . Information Visualization. Ajit Nema Director, Deloitte Consulting. Information Visualization: What is it? . Interactive visual analysis of information to yield more insight, more action, and more effective decisions.

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Visual Decision Making

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  1. Visual Decision Making Information Visualization Ajit Nema Director, Deloitte Consulting

  2. Information Visualization: What is it? Interactive visual analysis of information to yield more insight, more action, and more effective decisions

  3. Total Fertility by life expectancy in China, India and the USA, 1950-2050 • Huge amount of data • Multidimensional data analysis • Total fertility rate • Life expectancy at birth • Across 50 years • Co-relate across countries • Traditional ways will requires multiple pivots and big spreadsheet or multiple graphs

  4. Total Fertility by life expectancy in China, India and the USA, 1950-2050 Source: World Population Prospects, the 2008 Revision. United Nations, Department of Economic and Social Affairs (DESA), Population Division, New York, 2009. See: www.unpopulation.orgNote: Total Fertility (TFR) is the average number of births per woman

  5. My Kitchen Remodeling – Visual Decision Making

  6. Information Visualization: It is not new!

  7. Information Visualization: Evolved over a period of time • Pre 17th Century • Maps and Navigation • Informational Diagrams • 17th – 18th Century • World Maps • Astronomical Visuals • 19th – 20th Century • Polar Area Charts • Bar and Pie Charts • Current Day • Visualization Methods for Real Time Data • Explorative Data Analysis • Tree-Maps and Network Graphs

  8. Information Visualization: What’s the Catalyst?

  9. Information Visualization: Success Stories • Usability Redefined • Innovative User Interface: Touch and gesture • Rich User Experience: Icons, Apps • Apple now dominates the mobile and tablet market • Interactive Multi-media Gaming • Intuitive motion controls and social gaming experience • Engaged people of all ages • Wii captured 47% of market in ’09 (source: IBIS Capital) • Personalized shopping • Puts shopper in the driver seat and allowed custom designs • E-Commerce sales ran ahead of all other channels in ’10 • Online sales increased 25%, surpassed 100m

  10. Information Visualization: What’s Different? Increased Scale Dramatic increase in computing horsepower coupled with advancement in computer interaction techniques enables handling larger data sets • Reports and analysis which used to take months to aggregate can be run in minutes • Modern visualization techniques can handle complex cardinalities and joins • More powerful computing enables multivariate analysis

  11. Information Visualization: What’s Different? Democratization of Data Visualization puts the power of data analysis in the hands of more organizational stakeholders Worldwide Growth Projection 2008 - 2012 • More intuitive drill-paths allow greater depth of analysis • Knowledge workers become more empowered as visual discovery tools become more powerful • Information becomes more pervasive and transparent across the organization Users Data Exabytes Devices (Units) Interactions (B-per day) 1.24B ~2.5E 416M 475B 3X 4.5X 7.7X 8.5X Servers PC Clients 442M ~4.7E 56B 54M Internet-Connected Devices

  12. Information Visualization: What’s Different? User Autonomy Information is making shift from being presented in a predetermined fashion to a malleable, versatile tool which stakeholders can readily use for decision making • Mixed environment of partially ‘pre-paved’ information but mostly self exploration of data by manipulating GUIs • Stakeholders who are closer to the front-lines have more access to analysis tools • Overall shift from passive presentation to autonomous, active discovery

  13. Information Visualization Approach & Techniques

  14. Traditional ways: Excel, Pivots, Reports May lead to information fatigue PIVOTS Multi-dimensional pivoting leads to an explosion of combinatory possibilities for analyzing data. A 3-D space with an average of 100 values leads to a whopping one million combinations to browse through. EXCELS Reams of rows and columns must be analyzed in order to interpret what are usually a few main business decisions. REPORTS These are much like Excel spreadsheets, but without the functionality. Some are designed to provide just-in-case information, they rarely address a business problem DASHBOARDS: Dashboards suffer from data aggregations which balance out important variations in the underlying data.

  15. Mashup: Hurricane Irene web monitoring • Mashup of disparate data required to analyze the complete information and make effective decisions • Pull in multiple feeds that will allow the client to see how their stores and logistics will be impacted over the next 72 hours

  16. Relationships in the data: patient drug prescriptions Each row represents the drugs a patient took in a specific quarter 500 1000 1500 2000 2500 3000 Patients 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 Drugs

  17. The same patient drug data, co-clustered Here the rows (patients) and columns (drugs) are clustered to reveal usage patterns Patients on Reyataz, Truvada, & Norvir Patients on Atripala only Patients on broad mix of Truvada, Norvir, Isentress, Intelence, & Prezista Norvir Reyatez Truvada Atripla Isentriss Intelence Prezista

  18. Network Analysis –who are the influencers Each doctor is a blue circle whose size is proportional to the amount of drugs prescribed Doctors are linked if they share an organizational affiliation or have common patients The thickness of the edge is proportional to the number of shared patients The three red dots are individuals thought to be key influencers This network graph shows that others may be equally or more influential

  19. Information Visualization: Additional techniques Tree Map Newsmap is a live visualization of Google news: a tree map algorithm fills the available screen space, as size denotes the importance of specific headlines, colour distinguishes news categories, and brightness the story novelty. Heat Map Explore the behavior of your visitors with a heat map. More popular sections, which are clicked more often, are highlighted as “warm” – in red color. MindMaps Informationarchitects.jp presents the 200 most successful websites on the web, ordered by category, proximity, success, popularity and perspective in a mindmap. Apparently, web-sites are connected as they’ve never been before.

  20. Trends In Information Visualization – Technology Spectrum JAVA Microsoft .Net E.g. WPF, Silverlight Animated IOS4 MOSS Excel Services Adobe Flash/Flex Data Management & Statistical Packages SQL Reporting Services Custom RIA Dev E.g. ECB’s FlexCB MS Office & Add-Ons E.g. Excel & IMF Map tool HTML 5 Level of Interaction BI & Data Viz Tools E.g. Xcelsius, Tableau Dynamic Web Design Tools E.g. Adobe CS Publishing Software E.g. Adobe InDesign Authoring Tools E.g. Freelance Static Paper Web Desktop Physical Media

  21. Information Visualization: Challenges • Handling complex and heterogeneous data formats and data sets • Combining available techniques for specific tasks in a canonic way for clustering, filtering, dimensionality reduction. • How to effectively present more than three dimensions of information in a visual two dimensional graphical display • How to effectively visualize data that is changing rapidly (as fast as several hundred thousand times per second)

  22. Information Visualization: Where to start? • Define the Business Purpose First • Know Your Audience • Invest in Data Quality • Explore Several Platforms • Assemble Specialized Team with Expertise in User Experience

  23. References • Deloitte Technology Trends 2011 • http://www.smashingmagazine.com/2007/08/02/data-visualization-modern-approaches/ • http://download.intel.com/pressroom/kits/events/idffall_2009/pdfs/2009_IDF_Otellini.pdf Analytics and Life Sciences

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