Using graph database to connect and enrich diverse data at scale, rapidly and cost effectively using data curation and machine learning algorithms.

In the real world, the process of preparing data for any type of analysis, but particularly machine learning, consume the majority of the time.

What is data curation?

Digital curation is the selection, preservation, maintenance, collection and archiving of digital assets. Digital curation establishes, maintains and adds value to repositories of digital data for present and future use.

Here is a video of curating the traditional SQL data in a graph database:

Why use machine learning?

Costs models and studies on digital curation costs constantly identify humans resources as the most costly component of digital curation.

The biggest cost associated with the initial setup of a data warehouse for machine learning applications is often cleaning up the data.

So some data problems never go away…they just scale.

Click here or on the Download button to see our presentation explaining Project Cortex: