I just had chance to play with a fantastic data visualization tool from IBM: Many Eyes. You can upload data sets or use data sets that others have uploaded to create all the regular visualizations (charts, etc), but also maps and treemaps, like this one that I built from party registration information in the early 2008 states:


The big blobs are states (Iowa, South Carolina, New Hampshire, Nevada). The size of the blobs represents the number of registered voters in 2004. You can see the small county boxes inside the states, showing the number of registered voters in each county. You can then zoom in on a state to see just the counties within that state. Within New Hampshire, I had town-level data readily available, so you can soom in to a particular county and see the towns in that county.

As a user, you have the power to easilly click away and play with the data in a way that emailing you a PowerPoint chart will never give you. You can play with the chart and explore the data by changing almost anything about the chart:
  • The colour of the shading currently shows the number of democrats. You can change it to republicans, or independents at the flip of a switch
  • The size of the boxes are the number of registered voters. Again, you can change it to be the number of republicans, or independents at the flip of a switch
  • You can change the sorting from State > County > Town to sort instead by County, or by Town
Isn't this a great way to let someone explore complex data? I love it!

The site's purpose is to "harness the collective intelligence of the net for insight and analysis." This sounds like a great goal. The thing I'm really interested in is that it allows someone to gather some neat data and easily visualize it in novel and interesting ways that others can tweak. Power to the people, indeed.

Is this the start of the end of sending a pack of PowerPoint charts? Instead hopefully we'll soon be able to quickly and easily send links to online visualizations that users can play with and get a feel for. Lets hope this is just a first step in this area.
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  1. I gave a talk at the Big Data Insight Group in London recently and they've just posted my talk online.


    I talk about how we've helped EMI Music make use of data and about how we're doing so in zeebox.

    One of the themes throughout my talk is the importance of people. Both in terms of how we use data to help people make decisions and about how we need to understand the people we're trying to help, in order to give them what we need. Technology enables this, but without the right people and without understanding people, technology is as good as useless.


    I also talk about how important skills and judgement are. And that, although it's sometimes seen as the things that drives decisions, it's usually or perhaps always used alongside skills and judgement. 


    I think that admitting to the role of skills and judgement isn't being 'anti-data'. I think that being honest about this enables and empowers us to better use data in the right ways. And it certainly helps people to feel comfortable with data, also!

    With the right people in place and data playing the right role in an organisation, the opportunity for data to help an organisation is massive. The way that EMI Music has embraced data across the organisation alongside skills and judgement shows that this is the case.


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  2. We all know there are decisions where you need data to help you make them and there are decisions where data just isn't that important. This morning XKCD did a wonderful job of illustrating it. http://xkcd.com/1036/

    Buying a lamp is a creative decision. Turn your eye away from the reviews and go with your heart :)

    The same is true of many decisions data folks are asked to help with every day in organisations. We shouldn't be afraid to champion this strategy there, either!

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  3. We sat down recently to talk data and insight. Here is what we talked about, plus a little video of me talking about insight at both zeebox and EMI.

    http://www.thebigdatainsightgroup.com/site/article/david-boyle-emi-zeebox-data-driven-includes-video
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  4. I don't like the term 'scientist' as it makes the role sound unaccessible and elite. Google's Hal Varian said "the sexy job in the next ten years will be statisticians" ... but I don't like that term either. I'd replace 'statisticians' with 'working with data' or something ... and then I believe it!  I think data people have a tendency to overplay the role of the 'statistics' and magic of it and underplay the importance of the 'bringing it to life' and 'helping people understand / make use of it' parts of working with data.

    I thought about this because of this cool article in The Guardian about data scientists.

    As it points out, "science" is defined as "systematic study of natural or physical phenomena". I guess that's us all. Perhaps I shouldn't shy away from that phrase.

    The journalist describes the role well, as "someone who can bridge the raw data and the analysis - and make it accessible. It's a democratising role; by bringing the data to the people, you make the world just a little bit better." Perfect, eh?

    One last quote: "the four qualities of a great data scientist are creativity, tenacity, curiosity, and deep technical skills." That list sounds pretty good to me, also. So perhaps I should rename this the 'data scientist' blog and be done :)



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  5. Some fun from http://fosslien.com/ via http://www.freakonomics.com/2012/02/29/the-life-of-the-number-crunching-analyst/


    I particularly like this one:

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  6. So much data, so easily displayed in such a small but easy to understand format. I need say no more. I'm in love with the new sparlklines just made available in Google Spreadsheets: http://support.google.com/docs/bin/answer.py?hl=en&answer=2371371


    It's this simple:

    Google Spreadsheets is rapidly becoming my go to choice for building business dashboards. Bye, bye cost. Bye, bye developers (would be VERY sad not to work with them, of course). Bye, bye Microsoft!

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  7. I spoke on a panel last night on the subject 'data as the new black gold'. There are three challenges I think this metaphor poses to the data world.







    First, that of crude oil. Data is everywhere in organisations, but too often left in it's crude form: gloopy and unusable. The oil industry had to work this out before it could be mainstream. It had to refine oil to a form that works for consumers day-to-day and it had to make it available to consumers in ways that fitted in to their daily life. It's trivial to stop by a petrol station and pick up some oil in a format you can instantly make use of. Data doesn't yet work the same way: it's rare to find an organisation that appropriately refines it and then makes it available to it's people in a way they can access and make use of as part of their day-to-day work.


    Second, I think we need to demand higher 'miles per gallon' from our data. Often we gather fantastic raw data, capable of being a really powerful part of decision making ... but then business leaders don't ask interesting questions of it. They don't demand smart analysis and challenge the data to offer insight. It's like demanding that cars offer higher miles per gallon from the oil they are burning.


    Finally, I think we need to embrace hybrid technology. In cars that's about oil being only part of the story for how the car gets powered. In data it's about saying that data is only part of the story for how organisations get powered. We need to be honest and bold about the role of skills & judgement alongside data in powering organisations. Too many people believe / pretend that data alone can power organisations to greatness. Everything I've seen tells me that data is necessary but not sufficient: smart people to use the data alongside their expertise is ALWAYS required. The data world should be honest about this and build data and systems around that truth. I've always found that has a much greater impact :)
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  8. I've used a lot of word clouds recently. But I think of them as charts really, since they are still pretty faithful to the underlying data. The size of the word is proportional to the number of times that word is in the data set. Simple.

    But reading a cool data visualization book I came across this. Really it not based on 'data', but it's interesting his words and their location on the page conveys such a lot of information. Perhaps some good, well placed words can replace the need to chart actual data?

    http://creativeroots.org/2011/03/italy-infographic-map/
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  9. Simple, easy to read, but really powerful. Nice little sparklines spotted in the papers from the 20 week scan my wife just had. Cool little chart like this should be everywhere!

    And by the way, it's a boy!
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