Visual analytics: Aimless wandering or Systematic data exploration

With great power comes great responsibility.

One of my favorite quote from movie Spider-Man which was sourced by Stan Lee, famous American writer and editor. After working with visual analytics for three years I realized that this quote is utterly correct for visual analtycis. Visual analytics is a new exploratory paradigm which combines visualization, human factors and data analysis. Human factors such as interaction, cognition, perception play central role in the final outcome of the analytics and decision making process. Visual analytics is great and powerful tool but it requires a systematic approach to discover the unexpected. If your efforts are not well organized then probably your are anticipating aimless wandering. Due to latest technological advances now we are generating massive amount of complex data and finding useful information out of these data sets is like searching for needle in haystack. So how can we make best use of technologies like visual analytics to increase the probability of discovering something out of the blue, before that we need to ask what is visual analytics and what is not, and how to optimize the human factor in this process.

What is visual analytics and What is not
Visual analytics is an exploratory funnel, very much like folding funnel (a specific version of the energy landscape theory of protein folding), and to reach the endpoint of the this funnel (which is nothing but discovery) we have to go through many intermediate states. As expected one need to explore this space before making any move, at the same time we have to minimize our efforts. So it is not just visual analysis, but it is more visual exploration providing better insight about data.

visual analytics exploratory funnelOne of the biggest myth with visual analytics is that it makes discovery easy and faster, which is not true, although probability of discovering unexpected is niftier. Most of visual analytics tools have very sharp learning curve, and it is essential to cover the basics adequately before diving into advanced methods. Each visual analytics technique is composed of interactive visualization, but not all interactive visualizations are visual analytics. This is very common mistake to use phrase visual analytics for normal visualization. A visual analytics tool must establish a communication between user and visualization, for every action there should be a reaction, which force analyst to ask more questions by synthesis of visual reasoning. There is no such thing that visual analytics can be used with only complex and massive amount of data, visual analytics is scalable technique and allow to explore basic as well as composite problems.

Why visual analytics



Role of guided visual analytics

Generally complexity of visual analytics systems demands high-end analyst to solve analytical problems. There is extensive discussion about what should be scope of visual analytics, currently it is a complex analytical technique for sophisticated users empowering their specialized needs. How it can help casual users to solve not only their specialized problems but also their basic requirements. This problem can be solved by guided visual analytics workflows which gives ability to easily arrange a sequence of analysis steps into a workflow template that can be edited, reused and distributed. In guided visual analytics specialized analysis workflows are created by high-end analyst and later these workflows can be passed to casual users making their life easier. This allows end users to address key analytical questions without needing to learn the advanced visual analytics techniques nor it requires to become an expert user. Guided analysis workflow are easy to use and give more insight by providing easy access to advanced visual analytics techniques. Guided workflow is best way to optimize the human factor in visual analysis process.

Visual analytics not only to permit users to detect expected, which might be captured by any other analysis tool such as different data mining applications, but also to help users discover hidden patterns, and relationships in complex relational data. Of course if data is not very complex there is no reason that you can not find all patterns using another tool, but when data is large and heterogeneous it become hard to follow conventional analysis systems, but this hidden discovery does not come for free. Currently the visual analytics software cost a lot which is one of the reasons that people are less aware about potential applications of this technique. Before acquiring any visual analysis systems you must realize your requirement and the full potential of the visual analytics systems.

List of Visual Analytics Tools

  1. TIBCO Spotfire
  2. Tableau
  3. IBM Many Eyes
  4. Jigsaw
  5. GeoWizard Lite

Only Spotfire and Tableau are full featured visual analytics tools.

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7 Responses to “Visual analytics: Aimless wandering or Systematic data exploration”
  1. anilbioma
    02.24.2009

    Interesting observation about VA, especially comparison with folding funnel. When I started working with VA, I was confused cause it was going on every direction so it took time to understand what to avoid. An analysis plan must be drawn before we start interacting with VA. Still the industry standard softwares such as TIBCO Spotfire and Tableau can cost anything above 1000 US$ per seat, thats very costly considering I can do most of things in R.

  2. 02.24.2009

    Ya that’s true, apart from associated higher cost there are issues such as software deployment, take a example of Spotfire that is not easy to install as it is targeted to enterprise users. So make it easy to buy, easy to learn and easy to deploy then people can realize true potential of techniques like visual analytics and that’s how it will grow.

  3. 02.25.2009

    Aimless wandering or Systematic data exploration
    http://tinyurl.com/cowjs9

  4. 02.25.2009

    Visual analytics: Aimless wandering or Systematic data exploration: With great power comes great responsibility… http://tinyurl.com/cowjs9

  5. 02.25.2009

    reading Visual analytics: Aimless wandering or Systematic data exploration http://is.gd/kPFj

  6. 02.26.2009

    Visual analytics: Aimless wandering or Systematic data exploration

    http://tinyurl.com/cowjs9

  7. 08.13.2010

    Visual analytics: Aimless wandering or Systematic data exploration | Abhishek Tiwari http://bit.ly/aOORGn