Like “pivot” and “cloud computing,” “big data” is one of those startup buzzwords that gets thrown around indiscriminately–partly because it means different things depending on the intel you’re trying to unearth and partly because it sounds like the kind of futuristic jargon that opens doors. Using machine learning to analyze big data? We can practically see the pitch deck already!
As The Economist noted back in 2010, the deluge of large data sets unleashed by the digital age, “makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account.”
If you spend as much time on CrunchBase–the wiki database launched by TechCrunch in 2007–as Betabeat does, it’s dawned on you that for such a valuable resource, it sure is hard to organize data in a meaningful way. Around the time of CEO Heather Harde’s departure from TechCrunch, we seem to recall tweets (that we can’t find now!) about how AOL, which purchased CrunchBase as part of the acquisition, better not mess it up. And they haven’t. But they haven’t really given users features that leverages its juicy stacks of data either.
Which brings us to SeedTable, a new site that uses CrunchBase’s API to build a new, uber-practical interface. The project was put together by Imran Ghory, the London-based founder of CoderStack. You can now sort data by sector, most active cities in the last 12 months, or historical activity, which shows the number of companies founded versus the number of exits. You can also sort data by, say, top angel investors by investment count in New York City.