Data Curation

I keep running into startups that are using crowd sourcing to cheaply aggregate data, with an aim to disintermediate incumbents and to figure out a business model once they have enough customers.

However there are some segments where data is not currently threatened by the crowd at all.

Generally this is where data needs high levels of curation to be useful and also where data holes or data mistakes add too much risk for the users.

Examples are data purchased by corporations upon which critical decisions are made, such as market share and competitor information and patent data.

There is however an analytics opportunity out there to compare crowd aggregated data with curated data, to put a fair market value on both sources of data subject to use cases and inherent risk profiles for the users of the data.