Building data startups: Fast, big, and focused (O’Reilly original)
Republished by Forbes as:
Data powers a new breed of startup
Based on the talk Building data startups: Fast, Big, and Focused
by Michael E. Driscoll
From the post:
A new breed of startup is emerging, built to take advantage of the rising tides of data across a variety of verticals and the maturing ecosystem of tools for its large-scale analysis.
These are data startups, and they are the sumo wrestlers on the startup stage. The weight of data is a source of their competitive advantage. But like their sumo mentors, size alone is not enough. The most successful of data startups must be fast (with data), big (with analytics), and focused (with services).
Describes the emerging big data stack and says:
The competitive axes and representative technologies on the Big Data stack are illustrated here. At the bottom tier of data, free tools are shown in red (MySQL, Postgres, Hadoop), and we see how their commercial adaptations (InfoBright, Greenplum, MapR) compete principally along the axis of speed; offering faster processing and query times. Several of these players are pushing up towards the second tier of the data stack, analytics. At this layer, the primary competitive axis is scale: few offerings can address terabyte-scale data sets, and those that do are typically proprietary. Finally, at the top layer of the big data stack lies the services that touch consumers and businesses. Here, focus within a specific sector, combined with depth that reaches downward into the analytics tier, is the defining competitive advantage.
The future isn’t going to be getting users to develop topic maps but your use of topic maps (and other tools) to create data products of interest to users.
Think of it as being the difference between selling oil change equipment versus being the local Jiffy Lube. (Sorry, for non-U.S. residents, Jiffy Lube is a chain of oil change and other services. Some 2,000 locations in the North America.) I dare say that Jiffy Lube and its competitors do more auto services than users of oil change equipment.