Tamr (formerly Data-Tamer) has emerged out of stealth mode with series A funding and an offering in the marketplace – a $16M+ funding round led by Google Ventures and NEA and is closing a lineup of enterprise customers that include Thomson-Reuters, Novartis, Glory Jeans and more. The startup – the brainchild of database industry pioneers and entrepreneurs Mike Stonebraker and Andy Palmer – is the latest to enter the data preparation sector with a machine learning-based approach to the issue of ensuring that data, in a variety of formats, is ready for analysis. More specifically, Tamr is looking to take the heavy lifting out of the attribute mapping and recording matching process for semi-structured and structured data, using an enterprise-oriented multi-tenant cloud service designed for data scientists.
Palmer is a serial entrepreneur who has helped found, advise and/or fund more than 50 companies in technology, healthcare and life sciences. In addition to Tamr, he runs Koa Labs, a start-up club in Cambridge. He also co-founded big data analytics pioneer Vertica, which was acquired by HP in 2011.
Tamr helps big companies organize sloppy data sets with the aid of algorithms and human guidance and do the dirty work of organizing all kinds of data that would take an individual thousands of hours to sift & sort. Tamr is addressing a huge problem for big companies with data mixed up and housed in a variety of locations and in need of organization before it can be analyzed for insight and action.
A recent industry research report from 451 Research makes the following observations about Tamr:
As we have said before in our Total Data Integration report, semi-structured information needs to be united with structured data in order to provide insight, which wasn’t possible or present when only focusing on the integration, mapping and matching of data of the structured variety. With its sterling management pedigree, cloud service designed to serve a genuine market need, and financing to further product development, Tamr is off to a strong start. However, it is entering an emerging field courted by other new breeds of data management players, which will not offer quite the same thing and are similarly focused on serving analysts’ data preparation requirements at scale and on diverse data types.”
Studies show that today, due to the cost and complexity of connecting and preparing the vast, untapped reserves of data sources available for analysis, most organizations use less than 10% of the relevant data available to them. Palmer and his Tamr co-founder Mike Stonebraker, (database scientist and MIT professor) believe that if the industry is going to be successful at managing the growth and variety of data that lies ahead, a complete overhaul of traditional methods of information integration and quality management will be required.
If your company is big enough to have more than one data scientist, you’ve probably got a lot of data sources to work with. Tamr is in the business of making connections between those various sources, whether they’re internal or external. Tamr uses advanced machine learning to combine hundreds or even thousands of data sources. It crawls all the available data then makes recommendations on how to blend them.
In the VentureBeat video below, Palmer explains how every business needs to curate all of its data sources to “make better decisions every single day” — and why Tamr’s “secret sauce” of machine learning plus human guidance can help enterprises curate data with great scale and precision.
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