Analytics startup Precog to make analytics on unstructured data as simple as possible with a new line of targeted appliances.
One early customer is using Precog to match up resume data with job openings, which is a tricky proposition in a relational format because resumes can include so much personalized information or content that doesn’t fit into a schema.
Precog supports Quirrel, a simple query language designed for analyzing JSON data and to do everything that SQL can do, also including statistical analysis and easy machine learning.User can build queries on JSON data with Labcoat (a visual query builder), and export them as code that run in the programming language.
Precog can store any kind of JSON data, from primitive values, to records, to complex, large documents with lots of nested objects and arrays. Precog does not impose any schema on data. Every value you store in Precog can be different from every other value. Developer-Friendly APIs for everything, including ingest, queries, and security, accounts and API keys, and client libraries for all common languages. Helps to build queries on your JSON data with Labcoat, a visual query builder. Do everything from data munging to analytics and machine learning.
Check out www.precog.com