Graph Theory and Analytics - Understanding its Business Applications

Friday 16 April 2021

This event has finished.

Started 16:00 PM

Finished 17:30 PM

Organized by ODSC Lisbon Data Science

Venue: Online/Virtual

Address: Online event on your device
8600 Lisboa

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Topic: Graph Theory and Analytics - Understanding its Business Applications

Speaker: Emeka Okoye, Chief Semantic Architect/Knowledge Engineer at CYMANTIKS Nigeria Limited

He is a Knowledge Scientist with Cymantiks Limited, In the last 25 years, Emeka has been at the forefront of technology and innovation in Nigeria from co-founding the earliest startup ( to designing the first framework for publishing Open Election Data to building cognitive solutions like Knowledge Graph for public sector corruption.

His experience has embraced a breadth of technologies culminating today in the Semantic Web and AI world with his primary focus being solution design, engineering and product development while working with a cross-section of professionals across various cultures in Africa and Europe in solving problems at a complex level.

He has been listed among the top 20 most influential Technology people in Africa (2013) by South Africa IT News blog and also among the Global Top 20 Mobile Commerce, Mobile Payments, Mobile Banking and Mobile Money influencers in Social Media by Obopay (2012).


Visualizations are a powerful way to simplify and interpret the underlying patterns in data. It is incredibly useful and helps businesses make better data-driven decisions. Use of graphs is one such visualization technique.

Graphs are mathematical structures used to study relationships between objects and entities. These entities can be either customers, products, operations, or devices. Graphs are leveraged mostly in social network analysis, fraud detection, supply chain, and search engine optimization. By mapping these relationships in connected data, graph analytics is used to unlock more insightful questions and produce more accurate outcomes.

We can use Graphs to model different structures and problems in an efficient manner and it provides a mechanism to do that in cases where the data is arranged in a specific way.

Learning Objectives:

1. An understanding of Graph Theory

2. What graph algorithms are and their Practical applications

3. A broad overview of the field of graph analytics to learn new ways to model, store, retrieve and analyze graph-structured data.

4. And much more

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