We've been introspecting somewhat over the past few weeks as to our identity; what it is that makes Atheon Analytics... Atheon Analytics. A clear definition is emerging, but it has taken all of us a little time to understand the impact of a clear identity.

Whilst musing on this, and catching up on Stephen Few's excellent blog at Perceptual Edge, I came across an article referring to a video by Bret Victor. It focuses on Bret's principle that "... creators need an immediate connection to what they're creating." - a concept that resonates strongly with we data pioneers.

The result, is an impassioned  plea to live one's life with a sense of purpose, identity and principle. I hope you find it inspiring too.

AuthorGuy Cuthbert

This week I (Guy) have been over in Washington DC at the invite of the Visual Analytics Community to participate in the 2011 Conference. The attendees were mostly US-based researchers and government representatives, plus a handful of industry/commercial types - making for an interesting mix; the US government personnel as the primary 'customer' for much of the work under discussion, with the academics as the primary practioners.

I was invited by the VA team at Middlesex University to join a panel discussion on "Visual Analytics in Practice", alongside US practitioners from industry, government and academia.

My presentation, themed as "tackling the 'too tough' problems in retail and consumer goods" can be seen in the video below:

The panel session itself was very interesting, touching on the requirements of the US National Archives and Record Administration (needing to explore billions of legal documents and emails), analytical learnings at Boeing (including an excellent definition of different types of analytical activity - I hope to cover these in a future blog) and use of Visual Analytics in the retail and consumer packaged goods sectors; despite significantly different domains, key benefits and challenges shone through:

  1. All parties noted huge productivity gains from the use of VA techniques; most describing complex tasks shrinking from weeks to days, or days to hours in some cases;
  2. There was strong agreement on the depth of understanding gained from the use of VA techniques, and that visual exploration left a greater impression on the explorer, and resulted in a more compelling argument presented;
  3. Everyone noted the emergence of a new breed of analytical tools, but concluded that a "one size fits all" solution does not yet exist in this nascent discipline.

The conference itself ran for two days and provided an opportunity for both requests for new tools and technologies, particularly from various sections of US government, and for researchers from universities and national laboratories to highlight new discoveries, software frameworks and analytical techniques. For me, the highlights were:

  • Alan Turner's work on dissecting the visual analysis process, and identify clear disctinctions between analytical activities; leading to better separation of tasks across teams, mentoring of indivudals and formulation of methodology
  • The 'paired analysis' approach of Andrew Wade and Roger Nicholson examining the interaction between subject matter expert and technical expert in joint visual analytics activities
  • David Kasik's classification of 'types' of visual analytics - making a distinction between different purposes, activities and tools/techniques to support operational and strategic analysis
  • Dave Wells closing presentation on the differences between, and emerging role of, visual analytics and traditional business intelligence

Once the relevant presentations become available online I will link them to the points above.

In all, a very useful trip - presentations received, people met and topics covered.  The next phase of the UK VAC kicks off later in May, and Atheon will be attending - subscribe to our RSS feed for news from that event.

We were asked, recently, to present to the global sales, marketing and supply chain presidents of one of our customers on what the UK business had achieved using visual analytics. This was a great opportunity, but preparing for the meeting led to an interesting question:

"What are the key attributes of the visual analytics applications we use which makes them great for visual analytics, which other software tools don't posess?"

On the face of it, this should be easy - they all offer great visualisation, of course... but this isn't unique to them (there are a great many visualisations available across a multitlude of tools). As we considered the question further, we realised that our approach to visual analytics - the Atheon way, if you like - is dependent equally on three key attributes.

1. Visualisation

Yes, visualisation comes first in the list. Visual analytics without visualisation is impossible, so we need to be able to present information in a visual manner, helping our audience to see the patterns in their data rather than try to calculate them.

Most of the people we work with, the audience for the work we do and the applications we build, are business people - very few are full-time analysts, and few have any substantial formal training in statistics. 

The tools we use - and the applications we build with them - start with visuals, and enable the user to explore those visuals before attempting to quantify precise values through data tables. Traditional business intelligence tools - spreadsheets included - start with tables of data and allow the user to create a visual representation here and there.

2. Interactivity


When an enquiring mind is presented with a clear visualisation, an improved understanding emerges... but the enuqiring mind immediately conceives another question which itself can be answered by a different, or altered, visual. Our aim is to serve up image after image to allow the user to explore their data as quickly as they think of questions; this high degree of interactivity - almost real-time in many cases - encourages deep engagement with the data and draws the user into a richer understanding.

Traditional BI tools do allow interactivity, but this can often mean slow round-trips to huge database servers, resulting in tens of seconds - even minutes - between questions. This slow response actively discourages the user from exploring the data, and leads to a limited understanding based on pre-canned reports. 

3. Data blending

Data Blending

Rapid interactive graphics enable the user to explore data at speed... and this leads to the third essential feature of the tools and techniques we use; data blending - the ability to stitch together different data sets, from different sources, in order to build the most complete and robust picture possible.

Despite the best efforts of IT departments around the world, much of the data that organisational users depend on resides in departmental spreadsheets, files received ad hoc from customers and suppliers, or drawn from an increasingly large range of sources on the Internet. It is impossible for IT to own and manage all of these data sources, and so traditional tools simply ignore them... this explains why so many expensive BI tools lie dormant, with data extracted in Excel and 'blended' through the high-risk vaguaries of VLOOKUP.

The tools we use can all access multiple data sources at once, encouraging the user to merge different data sets to create rich combinations that provide the best view of the problem, or opportunity at hand.

For more about the tools we are talking about, take a look at our product comparison.

AuthorGuy Cuthbert