February 2, 2015

Extras: More analytics news

By Paul Laughlin

Stand_Studio_Geek_-_Monaco_Anime_Game_Show_-_P1560500This week there seems to have been more analytics in the news than usual, so despite the earlier post on Analytics awards & trends, I’m going to share another ‘other’ post round-up on this topic.

First to catch my eye was the news that Microsoft has purchased Revolution Analytics.

This is interesting not just because it adds to Microsoft’s analytics arsenal, all of which have the potential to benefit from integration with the rest of Microsoft’s technology (including Office), but also because of the focus on R. In an earlier poll we identified the rise of R as an alternative to the more popular SAS & IBM analytics software currently used by insight teams. Revolution Analytics already provided commercial support & simpler front-end to R, integration with Microsoft’s other software has the potential to take this further towards being a mainstream contender (hopefully not at the loss of affordability). It’s also interesting in this article to hear how popular R is as a language for data scientists within Microsoft (including those working on Xbox Live service).

In other analytics news, further along the techie/geeky end of the scale, is news of Project Jupyter. No, this isn’t about Galileo or plans for missions to the planet Jupiter, rather its another open source software project which is working to bring together in one tool the ability to use the R programming language mentioned above and others that appeared in our poll, like iPython (and another one called Julia). This isn’t just about nerds having another cool toy that allows them to ‘geek out’ with their favourite coding though, it is thought that combining the different strengths of these data manipulation languages will help overcome current barriers to analytics in diverse environments. What I mean there is both analytics directly on web data & the growing number of businesses who choose to use Hadoop or other tools to connect disparate data sources rather than bring them all together. These types of really big data can present new hurdles to analysts & Project Jupyter might just give them free tools to help.

Now I must admit that was pretty techie content, even for me. But if this gets you going & you’re looking for more cutting edge data science commentary, together with tongue in cheek ‘awesomeness‘ and some advice on good beers – then you might like this podcast. Not aimed our main readership, customer insight leaders within business, but hard core data scientists should love it:

Hope you enjoyed that, do tell me what you thought. Normal service will be resumed later this week, as we continue to focus on wider customer insight & leadership challenges. Have a great week.