From Disparate Data to Visualized Knowledge

A step-by-step guide for data ingestion, inference validation and visualization with GraphDB followed by GraphQL interface setup, search and federation with Ontotext Platform.

The recording of this webinar is available on YouTube.

No product arrives on the market in its final form. Updates are inevitable, and so are changes to the architecture. A small solution may rely on a simple manual system of ingestion. As the solution grows and becomes a proper product, this manual system evolves rapidly. First, data analytics are introduced, then automated and soon the data ingestion process itself is automated. “Evolution” is an important keyword here. Very often, solutions focus on transformations and tectonic shifts. However, in the best-case scenario, the product grows naturally and does not reinvent itself at each step of the process.

In this webinar, we will investigate a more natural approach to growth. The narrative will start at a manual data ingestion system, then it will look into unlocking this system’s true potential by integrating it with a knowledge graph. We will also cover automating the data gathering and transformation process and will finally look into integrating other systems.

This session is ideal for you if you have ever asked yourself:

  • Is there an easy way to use spreadsheets, but also keep a knowledge graph?
  • What approaches are there for dynamically ingesting data and modifying it, based on what’s already known?
  • How to deploy a high availability environment without employing many different tools?
  • How to best integrate RDF with other data sources?

Who is this webinar for:

  • Architects and product owners who are interested in growing their application without redesigning at each step.
  • Operations experts who want to explore deployment options for the Ontotext technology stack.
  • Data scientists who want to learn about some of the ways to visualize their hard work.

About The Speaker

Radostin Nanov

Radostin Nanov

Solution Architect

Radostin Nanov has a MEng in Software Engineering from the University of York in the UK and has been on board Ontotext ever since he graduated in 2016. He’s the maintainer behind the Ontotext Cognitive Cloud. Radostin also dabbles in DevOps, helping to spearhead Kubernetes development in Ontotext. When he gets the chance, he participates in core GraphDB development.