Intechiq

IQ Office/TigerGraph
Single Entity View Single Customer View

Getting to ‘True’ with Single Customer View

Let me introduce you to Mr Peter Jones.
According to my customer database, he lives at 16 Cavendish Street in the Sydney suburb of Stanmore. However, I also have a record of a ‘P Jones’, who supposedly lives at 1/6 Cavendish Lane in the Sydney suburb of Enmore.
In my database, I also have a record of a ‘Pete F. Jones’ purchasing one of my company’s products, and another transaction, recorded several months later, where a ‘PF Jones’ orders the same item.
Who are these multiple mysterious ‘Mr Jones’ personages who are apparently residing in close vicinity to one another in the inner-city suburbs of Australia’s largest city, and purchasing similar products from my company?
Would it surprise you to learn that they are actually one and the same person?

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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.

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Conference: Public Sector AI & Data Showcase

Showcasing TigerGraph graph database. Hotel Realm, Canberra, Tuesday 7 December 2021.

While online fraud continues to become more sophisticated, so too does the technology to detect it.

Modern day fraudsters and money launderers operate predominantly in the digital world, and for this reason the TigerGraph Graph Database has been designed to provide the deep, ultra-quick analyses of large datasets that is needed for real time fraud detection.

In a world that is doing business online at increasing volumes and speeds, a system that can filter out fraud in real-time will build all the trust you’ll ever need to succeed.

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Managing Risk and Preventing Fraud with Graph Databases

Managing Risk and Preventing Fraud with Graph Databases

by Terry Goodman, Founder of Intech Solutions

While online fraud continues to become more sophisticated, so too does the technology to detect it.

Modern day fraudsters and money launderers operate predominantly in the digital world, and for this reason the TigerGraph Graph Database has been designed to provide the deep, ultra-quick analyses of large datasets that is needed for real time fraud detection.

In a world that is doing business online at increasing volumes and speeds, a system that can filter out fraud in real-time will build all the trust you’ll ever need to succeed.

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TigerGraph Graph Database Chosen By Australian Tax Office

Australian Taxation Office becomes a TigerGraph customer

TigerGraph, the only scalable graph database for the enterprise, and Intech Solutions, a leading provider of information quality solutions, recently announced a multi-year deal with the Australian Taxation Office (ATO).

A graph database and graph analytics, provided by TigerGraph and implemented by the ATO with support from Intech, will help the ATO detect intricate and multi-layered relationships between individuals and organizations, supporting the ATO’s efforts to reduce tax avoidance.

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Graph database analytics for investigations and fraud detection

Video: Graph database analytics for investigations, compliance and fraud detection

Terry Goodman, Managing Director of Intech Solutions, delivered a keynote address on Graph Database analytics at the 7th Annual Australian Government Data Summit – 2021.

Terry included an interesting case study describing the Australian Tax Office (ATO) adoption of the TigerGraph graph database, a modern graph solution winning global applause for its unrivalled speed and scalability. You can view Terry’s full presentation in this blog.

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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.

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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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