From today forwards, the company behind RapidMiner will assume that product's name as its own, in honor of its other announcement: a successful $5M Series A funding round, with participation from European firms Earlybird Venture Capital and Open Ocean Capital (the latter firm having a strong pedigree from the team behind the MySQL relational database).
RapidMiner has been a profitable company, growing organically, since it began, according to its North American CFO/COO, Andrew Dinsmore. Dinsmore also explained to me that, with its new funding, the company will now be able to build out much more robust sales and marketing teams. Given that 2014 runs a good chance of being a big year for self-service predictive analytics, the timing of this capital injection seems very well-selected indeed.
RapidMiner's funding will also be used to build out the development team. While the product already offers a graphical user interface for building data mining/analytics workflows, future versions of the product will offer a more self-service-style interface for less technical, more business-focused users, and the processes it builds will be fully script-able.
RapidMiner is a German company, but will be moving its headquarters to Boston. Such a university-rich environment seems like a good place to go with the company building out its technical team. That said, RapidMiner's German pedigree is hardly an oddity in the space. Both SkyTree and KNIME (on whose open source data mining product the analytics functionality in Actian's DataFlow product is based) are German as well.
Alpine Data Labs' execs are not from Germany, but instead hail from Greenplum, Endeca, and ParAccel. Given those three companies' relatively recent acquisitions by EMC, Oracle and Actian, respectively, Alpine is looking a bit like the New School's University in Exile. Given that many of the professors at the latter were German emigres, I suppose Alpine has a German connection, of sorts, as well. But I digress.
As I've harped on earlier, data scientists don't scale, but RapidMiner and its competitors aim to make sure data science technology does, by packaging it in the form of self-service machine learning analytics products. Let's see how far they get in the coming year.