Data visualization representation of Analytics data

Data visualization representation of Analytics data

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  DATA VISUALIZATION PRASAD NARASIMHAN– Software Architect
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  MEANING • Data visualizationor data visualisation is a modern branch of descriptive statistics. • It involves the creation and study of the visual representation of data, meaning "information that has been abstracted in some schematic form, including attributes or variables for the units of information".
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  GOAL • The maingoal of data visualization is to communicate information clearly and effectively through graphical means. • To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way.
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  APPLICATIONS • Data visualizationis closely related to information graphics, information visualization, scientific visualization, and statistical graphics. • In the new millennium, data visualization has become an active area of research, teaching and development • Also been linked to enhancing agile software development and customer engagement.
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  ANALYTIC ACTIVITIES OFDATA VISUALISATION USERS
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  CHARTS USED FORDATA VISUALISATION Name Visual Dimensions Bar Chart  length  color Streamgraph  width  color  time (flow)
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   Treemap  size  color GanttChart  color  time (flow)
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  Scatter Plot  positionx  position y  color
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  EG :Visualizing MeteoriteImpacts • The data set was provided by The Meteoritical Society, an organization that has been documenting meteorites since 1933. • The data set received contained : • the name of each meteorite, • the weight, • the year when it fell or was found • as well as its coordinates
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  • Concept :material of the meteorite gives some hints about its origin, • After some research found that the types can be categorized into : • ‘stony meteorite’, • ‘stony iron meteorite’, • ‘iron meteorites’ and • in this case also ‘other’ which would include unknown and smaller groups of meteorites. • The overall dimensions included in the visualization is the : • types, • the location and • the size of the meteorites, which eventually was chosen to be shown in the first part of the visualization on the globe.
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  • Different colors wereused to clearly indicate the four categories of meteorites and their location shown on a map. • The second part would use the same categories but put them in a time perspective and point out the yearly amount of meteorites and what category they belong to.
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  • Eventually be projectedonto a globe showing all the continents and the meteorites as different sized dots and colors. • To do this an ‘azimuthal’ equal area projection was used in D3.js that would show all the meteorites and continents at once.
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  IMPORTANCE OF DATA VISUALISATION •When data volumes are very large, patterns can be spotted quickly and easily. • Visualizations convey information in a universal manner and make it simple to share ideas with others • It lets people ask others, “Do you see what I see?” And it can even answer questions like “What would happen if we made an adjustment to that area?”
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  COMMON TECHNIQUES • Understandthe data you are trying to visualize, including its size and cardinality (the uniqueness of data values in a column). • Determine what you are trying to visualize and what kind of information you want to communicate. • Know your audience and understand how it processes visual information. • Use a visual that conveys the information in the best and simplest form for your audience.
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  Modern approaches Displaying News Newsmap4is an application that visually reflects the constantly changing landscape of the Google News news aggregator. The size of data blocks is defined by their popularity at the moment.
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  Voyage6 is anRSS-feader which displays the latest news in the “gravity area”. News can be zoomed in and out. The navigation is possible with a timeline. Digg BigSpy8 arranges popular stories at the top when people digg them. Bigger stories have more diggs.
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  Digg Stack10: Diggstories arrange themselves as stack as users digg them. The more diggs a story gets, the larger is the stack. Time Magazine16 uses visual hills (spikes) to emphasize the density of American population in its map.
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  CrazyEgg lets youexplore the behavior of your visitors with a heat map. More popular sections, which are clicked more often, are highlighted as “warm” – in red color. Trendalyzer software (recently acquired by Google) turns complex global trends into lively animations, making decades of data pop. Asian countries, as colorful bubbles, float across the grid — toward better national health and wealth. Animated bell curves representing national income distribution squish and flatten. In Rosling’s hands, global trends — life expectancy, child mortality, poverty rates – become clear, intuitive and even playful.
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  Three Views showsthree views of the earth, in which each country is represented by a circle that shows the amount of money spent on the military (size of circle) and what fraction of the country’s earnings that uses (colour). Compact and beautiful presentation of data. Elastic Lists33 demonstrates the “elastic list” principle for browsing multi-facetted data structures. You can click any number of list entries to query the database for a combination of the selected attributes. The approach visualizes relative proportions (weights) ofmetadata by size and visuzalizes characteristicness of a metadata weight by brightness. Author’s blog34 regularly informs about new experiments in the area of data
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  Musiclens gives music recommendationsand presents your current mood and musical taste as a diagram. Spacetime59 offers Google, Yahoo, Flickr, eBay and images in 3D. The tool displays all of your search results in an easy to view elegant 3D arrangement. Company promises that the days of mining through pages and pages of tiny thumbnails in an effort to find the item you are looking for are over.
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  Munterbund39 showcases the resultsof research graphical visualization of text similarities in essays in a book. “The challenge is to find forms of graphical and/or typographical representation of the essays that are both appealing and informative. We have attempted create a system which automatically generates graphics according to predefined rules.”