Sep 23–26, 2019

Supercharging Elasticsearch for extended Knowledge Graph use cases

4:35pm5:15pm Wednesday, September 25, 2019
Location: 1E 14
Secondary topics:  BI, Interactive Analytics and Visualization, Data Management and Storage, Deep dive into specific tools, platforms, or frameworks

Who is this presentation for?

Product managers, analysts, architects, head of ITs, head of cybersecurity, anyone using or considering Elasticsearch

Level

Intermediate

Description

Drilldowns are the bread and butter of analytics. By using subsequent drilldowns to reach a result, one decreased cognitive load, improved sense of location during their search, and better understanding of their search result.

Information Retrieval engines such as Elasticsearch are well known to be great backends for explorative drilldowns and have been powering for more than decade data exploration in domains ranging from ecommerce to log analysis and more.

Elasticsearch however does not have relational join capabilities, so drilldowns cannot take “record to record” relations in consideration.

In this presentation I’ll introduce a plugin for Elasticsearch that adds cluster distributed joins and demonstrate how it enables an exciting array of use cases dealing with interconnected or “Knowledge Graph” enterprise data.

Thanks to these capabilities, and a lightweight semantic modelling layer, I’ll then show how at frontend level this allows one to move from simple “drilldowns” to “relational drilldowns” and also get network/link analysis.

As a result, Elasticsearch can be used to address at very large scale much higher value use cases in cybersecurity, fraud detection, law enforcement, intelligence and life sciences.

Prerequisite knowledge

Not much really, awareness of Elasticsearch is useful but nothing much is required.

What you'll learn

The audience has likely never seen "Relational" drilldown capabilities. Demonstrating Elasticsearch scale (and speed) navigation of interconnected data is a lightbulb moment for many, At theoretical level i'll explain how this is equivalent to navigating "enterprise knowledge graph" at scale, another interesting topic for many.
Photo of Giovanni Tummarello

Giovanni Tummarello

Siren

Giovanni Tummarello, Ph.D is founder and Chief Product Officer at Siren.io. Previously academic team lead at the National University of Ireland Galway, he has over 100 scholarly works on knowledge graphs, semantic technologies and information retrieval as well several startups and active open source projects started from its research, among which the top level “any23” Apache project, the Spaziodati.eu and Siren.io companies.

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