Intechiq

TigerGraph

Graph Databases Benefit Supply Chains

Searching for solutions to supply chain disruption? Graph databases may be the answer.

As the global COVID-19 pandemic runs into its third year, you would be hard pressed to find a business or individual that has not been affected in some way by the disruption that the virus has caused to global supply chains.

Now, as the virus continues to evolve and whole countries once again find themselves having to tackle new outbreaks, it’s clear that global supply chains are going to feel the ongoing impacts for a long time yet. For businesses everywhere, finding ways to successfully navigate these unfamiliar seas will be the new normal. ‘Adapt or die’ will be the driving principle.

Identity resolution with graph databases

Identity Resolution in Graph Data

Techniques for optimising data quality for identity resolution with graph databases

by Terry Goodman, Founder of Intech Solutions

A highly informative presentation that delves into modern techniques for optimising data quality for identity resolution with graph databases.

The content of the presentation includes:
* Introduction and definition
* Graph schema design(s) for identity resolution
* Transforming/parsing data to optimised schema design
* Enhancing data for identity resolution
* Identity resolution algorithms with graph.

The full presentation can be viewed in the attached article.

TigerGraph Graph Database

Event: Connecting the dots with the TigerGraph graph database

Reflections on Graph Analytics at the 7th annual Australian Government Data Summit

by Terry Goodman, Founder of Intech Solutions

The data analytics business is all about connecting the dots of particular situations without having to experience them directly.

One of the best ways of achieving this is with extremely fast, highly scalable graph database/analytics platforms.

Gartner estimates that the application of graph processing and graph database management systems will grow at 100 percent annually through 2022, “to continuously accelerate data preparation and enable more complex and adaptive data science.”

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