StartupWatch: A Trillion Line Spreadsheet -- Manipulating Big Data
New York based 1010data likes to ask: "What could you do with a trillion row spreadsheet?" because it shows off the capability its technology has in analyzing massive amounts of data.
Sandy Steier, co-founder of 1010data says that the trillion line spreadsheet approach to big data is a more useful way of analyzing large databases compared with a data warehouse approach. With 1010data's technology users can more easily identify patterns in data in days rather than months.
Some of the company's customers include large Wall Street firms. The turmoil in the financial industry following the crash of 2008 took away some large customers such as Lehman and Bear Sterns. "But the people at those firms went on to other firms or created their own, and so we managed to grow our business," says Mr Steier.
Customers upload their data to the 1010data platform and then perform their analysis. Table size is virtually unlimited, and one customer has loaded a 425 billion row table, or 0.4 trillion. The data is stored in the cloud which means that it is accessible from any location, enabling teams of analysts spread across different locations to work on the data.
In addition, there is no need for MySQL specialists to design and run analytics, the spreadsheet format gives users the ability to quickly change their lines of query without the need for days of planning to run queries.
Business is growing but there are some industries that aren't taking advantage of the tremendous amount of data that they have. "Telecoms hasn't yet tapped into all their data," says Mr Steier. Telecoms companies know a lot about their customers but they haven't acted on that data or built businesses around their data.
Every startup has to compete for the engineers and 1010data is no exception, and while recruitment is extremely tough in Silicon Valley, in New York it's not that bad. "For us it has gotten easier. Maybe because we've moved to nicer offices but also developers like to solve big problems and big data is a big challenge."