About this talk

Description

Most Major Companies are Exploring or Using Knowledge Graphs

Knowledge Graphs are at the top of the Garter AI Hype Cycle

But Knowledge Graphs are much more than hype!

Knowledge graphs are a mature technology used in large scale deployments.

Anyone heard of Google, Facebook, Alibaba, or Uber?

Knowledge graphs address major weaknesses in traditional relational technology.

These weaknesses are major drivers for silos, the bane of every enterprise.

Knowledge Graphs are being deployed in a large variety of industries, including financial services, information technology, health care & life sciences, manufacturing and media.

Common use cases include data harmonization, search, recommendation, question answering, entity resolution, provenance, & security.

Key Topics

What are Knowledge Graphs good for?
Supporting technologies
How can I get started?
What roadblocks should I watch out for?

Target Audience

Chief Data Officers
Data Scientists
Data Modelers
Technical Managers

Goals

Understand where and how knowledge graphs can add value to your enterprise
Know what supporting technologies are required for a typical knowledge graph deployment
Know how to get started on a knowledge graph application in your enterprise.
Understand what the current state of the art is and what is on the horizon.
Be aware of possible roadblocks to avoid.

Session outline:

Introduction
- Meet and Greet
- Setting the stage
Why Knowledge Graphs?
- What kind of problems can we solve by using knowledge graphs?
- What kind of problems are not best solved with knowledge graphs?
- How are knowledge graphs any better than relational technology?
- How do knowledge graphs address the problem of silos?
- What are some real world examples of knowledge graphs in the enterprise?
Putting a Knowledge Graph in Your Enterprise
- Where does the data come from to populate knowledge graphs?
- Who are the major vendors for knowledge graph technology?
- What are some common technology stacks used in knowledge graph deployments?
- What skills are required to deploy a knowledge graph application?
- Are the skills readily available in the workforce?
- What is the breadth and depth of tooling for knowledge graphs?
- How good are knowledge graph visualization tools?
- How well do knowledge graphs scale?

Format

Extended panel
Expert discussion, coordinated by moderator
2 hours running time
Running time includes modules of expert discussion, interspersed with modules of audience Q&A / interaction

Level

Intermediate

Prerequisite Knowledge

Basic understanding of Knowledge Graphs & Databases will be helpful

You need an access pass to attend this session: Diversity Access Pass or Full Access Pass apply

Categories covered by this talk

Semantic Technology

Knowledge Graphs

Workshops

Use Cases & Applications

Ashleigh Faith

Ashleigh Faith has a PhD, focused on Advanced Semantics, and she has worked in the search and data community for over 15 years with corporate business on eCommerce and Digital Asset Management, as well as government and manufacturing entities such as the Federal Reserve, John Deere, NASA, NATO, Gulfstream, DoD, and NLM on data strategy and knowledge management.

Katariina Kari

Katariina Kari (née Nyberg) is the lead ontologist for IKEA and an active semantic web practitioner for the past 5,5 years. Before that, she was doing the digital transformation for classical music. Katariina thinks the IT world is shifting from software to data and Knowledge Graph is a good place to be currently!

Michael Uschold

Michael Uschold has thirty years’ experience in developing and transitioning semantic technology from academia to industry. He pioneered the field of ontology engineering, co-authoring the first paper and giving the first tutorial on the topic in 1995 in the UK.

Mike Atkin

Michael Atkin has over 30 years of experience as a strategic analyst to financial institutions, regulators and market authorities on the principles, practices and operational realities of data management.