Recording – Introduction to Semantic Data Integration with GraphDB™

how-to-build-unified-data-layer-for-heterogeneous-silos-and-unstructured-data-with-graph-dbt_02

This webinar has been recorded and available on demand.

A major challenge for today’s enterprises is data integration: how to effectively leverage the data available both in structured and unstructured form. This unification process starts with the design and building of the semantic data integration layer, and ends with the application benefits.

Assembling all the pieces in a unified data layer, however, doesn’t have to be a daunting task.

We will show you how to do data integration with a single and very powerful tool – GraphDB – creating a unified data layer from heterogeneous distributed data as Linked Data.

As an introduction to semantic data integration and Linked Data in GraphDB, we will explain the benefits of this approach and why some of the most knowledge intensive businesses on Earth have chosen it, including:

  • Emblematic business cases and the value semantic data integration brings
  • Powerful examples of semantic data integration of data silos using Linked Data standards

After a brief introduction to Linked Data in GraphDB we will explain the benefits of this approach and why some of the most knowledge intensive businesses on earth have chosen it.

In this webinar, you will get first-hand experience on everything you need to succeed in your semantic data integration project:

  • Use GraphDB™ as an ETL tool to extract, transform, and load your data.
  • Enrich your data using semantic data schemas (ontologies), and derive new facts.
  • Explore your data with the available data visualization tools.
  • Query your data with a few simple yet powerful queries.

Finally, you have your hands full of reading materials and you will be given other opportunities for training & consulting on how to apply semantic technologies.

 

Webinar Duration: 60 minutes

Live Webinar: Yes

Live Question Answering: Yes

Resource After Webinar: Recording

petar_ivanov

Petar Ivanov has a MS in Machine Learning from University College London and a MS in Neural Systems and Computation from the ETH & University of Zurich. At Ontotext he is part of the Innovation and Consulting Unit and works on training and consulting services related to semantic technology integration, graph databases, LOD, ontology modeling, vocabulary & thesaurus management, semantic publishing platforms, text analysis & semantic annotation.

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