Graph databases are powerful tools in analytics, but they are an often-misunderstood innovation. As they hold the relationships between data as a priority, they are an invaluable tool for modern, heavily inter-connected datasets.

In this episode of Data Futurology, we explore graph databases with Peter Kokinakos (pk), the COO of MIP. They have been conceptualised for around 18 years, but it is only now that the computing power has started to catch up to allow graph database projects to come to fruition.

MIP is right at the front of delivering these capabilities to their customers. “It’s becoming a real product,” Kokinakos says in the podcast. “All of a sudden we’ve got the capability of delivering these really intricate kinds of analytics for complex relationships.”

Kokinakos, who will be speaking at the Advancing AI Sydney summit in August, further outlines the additional value that data scientists can get out of data relationship value in comparison to the data value. Delivering this value requires some change management to take advantage of because, as he says, “instead of just double clicking on something and drilling down the level, you can now actually drill down by the relationship.” However, once that change management process has been completed, the ability to be able to interact with customers on the basis of interconnected relationships rather than single data points is compelling.

Change management is a challenge for many organisations and data scientists – anything new is always going to have some resistance. This is why MIPS runs The Data School, and Kokinakos explains in detail the value that adds to customers in the podcast as well.

Tune in for an in-depth discussion into the very bleeding edge of data innovation with a company at the forefront of it.

Enjoy the show!

General info about the Data School

Application process and deadline for the next 3 intakes: https://www.thedataschool.com.au/apply/

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Read the full podcast episode summary here.