The end of Big Data?

The Cloud has eaten the three V's

What kind of scale is “Scaling Biotech” about?

In 2001, when Doug Laney coined the term “Big Data”, computer hardware was struggling to keep up with three types of scale: Volume, Velocity and Variety.

(More “V”s were added later, but that’s another matter.)

In the two decades since then, heroic efforts and massive investments have gone into addressing these problems.

Hardware got faster. Software got smarter. Cloud computing turned it all into a commodity.

Today, there are still a few cases where the 3 “V”s are a problem.

But not many.

“Scaling Biotech” is about a different kind of scale: organizational complexity, coordination across functions, communication across disciplines.

How do you make sure that your research program is more than the sum of its parts, as the number of parts grows?

How do you make data travel not just across a network but from one context to another?

To build a data platform that will enable your research program to scale, you need to know what kinds of scale you care about.

And most of them don’t start with “V”.