Big Data

A useful definition of ?big data? is data that is too big to comfortably process on a single machine, either because of processor, memory, or disk bottlenecks.

The problem that arises from having all of this data, bottlenecked at one or all of these points, is how to recover some of the cost of storage, and maybe even drive revenue, by using it to spot trends, derive insight, and so on.

You've got all the information that tells the story of your business, but no means to pull together a coherent narrative.

Big Data resolves all three bottlenecks by splitting your data across multiple machines, and managing queries across these machines.

At Alephant we can discuss your business as it exists in your data, develop useful questions, and demonstrate how you would go about turning your data into knowledge. Then it's up to you to turn that knowledge into wisdom, and action.

Quote at top of page appears in abstract of Bayes and Big Data: The Consensus Monte Carlo Algorithm (Scott, et al., 2013).