Siloed data is data that’s stored in disparate places, so people with questions about that data can’t put it all together to see the big picture.
In many spaces, the mere mention of siloed data makes an icy wind blow. That's because, without cohesive data, no number of fancy machine learning algorithms can create usable insights — or give a company an edge.
For example, companies and individuals in the commercial real estate industry need robust property information to make the best business decisions. That information is out there, but it’s scattered among various public and private data platforms, so it takes time to dig it up and piece it together.
Until recently, that is. A number of commercial real estate data platforms have cropped up, promising faster, more reliable information and insights.
One of those is Reonomy, an analytics platform that pulls data from outside sources and restructures it so it’s all visible in one place. Its billions of unique data points let it perform predictive analytics, such as telling users which properties are most likely to sell.
The company announced today a $60 million Series D round led by Georgian Partners, with participation from Sapphire Ventures, Wells Fargo Strategic Capital and Citi Ventures.
Through partnerships with data firms Black Knight, CoreLogic and Dun & Bradstreet, Reonomy compiles property data from county assessors, secretary of states, censuses, title companies, commercial data providers and geospatial companies. It runs that data through machine learning models, which can make predictions about properties based comparable ones. The platform can also tease out the real owners of different properties, as opposed to opaque LLC names.
Reonomy will use the funding to expand into Canada, the U.K. and other international markets, VentureBeat reported. Its total funding sits at $129.4 million, according to Crunchbase.
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