Finding Value in the Noise

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On Thursday 6th May 2021, Analytics Engines’ Chief Commercial Officer Brendan McCarthy and Chief Technology Officer Alastair McKinley took part in a webinar hosted by the Analytics Institute of Ireland.

During the webinar, they discussed the value of context and relationships in creating a “complete data picture”. They highlighted how the data cleansing process can often remove useful information and eliminate critical insights and intelligence capable of driving greater value from data.

Value in Noise

A Markets and Markets report predicts that between 2020 and 2025, the global market for Master Data Management (MDM) solutions and services will grow from $11.3 billion to $27.9 billion at a CAGR rate of 19.8%.

According to Gartner, MDM is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise’s official shared master data assets.

While certainly valuable in a variety of cases, and essential in others, a ‘Golden Record’ approach to data management can often eliminate critical insights and intelligence, hidden within an organisation’s data.

In many instances, insights are not derived from a single entity, but rather from the relationships that entities have to others. For example, the process of eliminating duplicate records can often sever relational links between peripheral data points.

By maintaining the integrity of the source data, organisations can find ‘value in the noise’ and develop a deeper understanding of how various entities within their data are connected.

MINERVA

During the webinar, we also showcased our Intelligent Search and Discovery platform, MINERVA. The platform enables users to explore the complex relationships that exist between siloed datasets. By maintaining the integrity of the source data, MINERVA enables users to find value in the noise.

Use Cases

Anti-Money Laundering

Using data from UK Companies House MINERVA was able to identify patterns of behaviour similar to those identified during the recent FinCEN investigation.

By maintaining the integrity of the source data, MINERVA was able to identify an individual who had hidden their activity by registering multiple different director profiles on UK Companies House. Each director profile contained minor variations in order to disguise the complexity and scale of this individual’s network.

A “Golden Record” approach to this challenge would likely have eliminated these duplicate entities, their relationship to each other and the patterns of potentially criminal behaviour. By using “source” data, that was augmented and structured in an appropriate way, MINERVA was able to establish a clear connection between these individual entities and create a comprehensive network of this person’s activity.

Corporate Fraud

A unique feature of the MINERVA platform is its ability to search for patterns and behaviours across siloed datasets as well as specific entities. This enables users to proactively identify and extract the critical business intelligence that matters most to them.

Using data from UK Companies House, and The Gazette for UK business insolvencies, MINERVA was able to create a pattern search that enabled us to quickly identify directors of insolvent companies, who had created new companies within 6 months either side, of their previous companies’ insolvency.

By enabling users to search their data based on patterns and behaviours, users can more quickly and effectively identify entities of interest, removing the need for time-consuming interrogation of large volumes of individual entities.

Public Sector Transparency

Using data from UK Companies House, and The Register of Members Benefits, MINERVA was able to identify Members of Parliament who directly benefited from the award of public sector contracts.

Similarly, we were also able to identify organisations that were awarded public sector contracts, whose board included individuals with notable links to the UK Conservative Party, both in terms of personal relationships and direct financial donations to the party.

Find out more

Analytics Engines are pleased to announce the launch of their MINERVA Early Adopter Programme. Interested individuals are invited to register for the programme by clicking the button below.

Register Interest

Arrange a Free Data Consultation.