dunnhumby takes 50% stake in Sandtable

We are delighted to announce that dunnhumby has taken a 50% stake in Sandtable.

dunnhumby is one of the leading customer science companies and we share with them a passion for using data to understand behaviour. It has been a privilege to work with them, pioneering the use of agent based modelling (ABM) with large scale individual data to uncover unique insights about consumers.

This announcement is a testament to what we have achieved together and our shared belief in what more can be delivered using ABM.

We look forward to talking more about our joint capabilities and what they can offer to brands and retailers in due course. In the meantime you can read about the partnership here and here.

PyData London MeetUp Launch

Pydata London had their launch meetup last night with pizza beer and python at Pivotal Labs space near Old Street.

Emylyn talked about issues of converting Matlab into Python with a particular look the domain of Phamacology and the Life Sciences.  What I found interesting were the big reasons for researchers in the life science to prefer Matlab to another tool like Python.  A company can pay a lot of money for something like Matlab and feel like they are getting guarantees and value for money.  Python is free, that could be worrying as far as getting quality and assurance.  Matlab has a huge 3rd party lib ecosystem in signal processing, hardware specific hook-ups to lab equipment, and synchronising large experimental trials.  Finally, for a scientist, Matlab’s syntax is closer to the language of math and is easier to express in terms of linear algebra (although there is interesting work with SymPy).  Also, it’s worth noting that for scientific computing Julia got a shout-out for being performative, but it’s also a young and growing language.

Jacqui from Flying Binary spoke about their “Mapping the Future” visualisation of tweets of data journalists.  She pointed out that if Gen Y is visual, then Gen Z (people born since 1993) is kinaesthetic, and what will absolutely be expected by that generation is interactivity.  Think about toddlers weaned on iPad interacting with a paper magazine.

Another twitter related talk was Giles who compared a MCL clustering with the Louvain clustering (a la Gephi) on a two-hop social network.  He found MCL to perform better, and that visual verification of large of graphs Gephi is super difficult.   He’s a big user of Neo4J (with Py2neo) as we are with our network modeling here at Sandtable.

Ben from Goldsmith is geeking out on scraping wordy beer reviews and with some NLTK and mining out key describers of beers.  What I found great was that he skipped the quantitative metrics that the users gave a beer and went straight for the text to create keyword clouds for a beer.

I also gave a lightning talk about my Kinect Stone project – using a Kinect to build a machine collaborative carving system.  With OpenKinect it’s a snap to get your kinect data out to numpy arrays.

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Finally, notable shout-outs to the OpenCorporates project and the PyLadies London chapter.  The Pydata (and Data Science in general) community is only growing in London.  Great work to the organiser’s of this Pydata Meet-up – Ian, Cecilia, and Emilyn !