Fuzzy Logix targets a $40 billion market with faster, cheaper big data analytics

Fuzzy Logix today announced a US$5.5 million series A funding from New Science Ventures, reports Tech in Asia

The traditional way to do analytics is to fetch data from a database, store it in separate file servers, create datasets, and use tools for data mining or predictive analysis on the datasets. Then the data is stored back in the database, and reports are generated on the analysis.

This works fine up to a certain level of data, explains Partha Sen, CEO and founder of big data analytics firm Fuzzy Logix. But when the records run into tens of millions and there are thousands of variables involved, as in predicting the chances of somebody getting diabetes, this becomes an inefficient and expensive process. Moving such huge amounts of data from database to dataset and back for each query takes a lot of time.
 

“When I was working in Bank of America,” says Partha – which is where he worked before founding Fuzzy Logix – “I found that analysts were spending time not so much in analysis but in simply moving the data.” 
 

The US-headquartered Fuzzy Logix, with a development centre in Bengaluru, India, has a flagship product called DB Lytix which embeds analytics within a database. So a query to the database can produce analytical results directly without the need to first extract a dataset. This not only saves time but also cuts infrastructure and manpower costs.
 

Fuzzy Logix today announced a $5.5 million series A funding from New Science Ventures to build up the R&D for its product and find new customers around the world. 

This is an excerpt from Tech in Asia. You can read the full article here.