Data Governance

The process of generating measurable economic value from data assets, either directly through licensing and sale or indirectly by using data to improve products, optimise operations, and inform strategic decisions. Data monetisation strategies are central to unlocking the full enterprise value of a company's information assets.

The processes, governance, policies, and technology used to ensure that an organisation's critical shared data entities — such as customers, products, suppliers, and accounts — are accurate, consistent, and controlled across all systems and business units. MDM creates a single trusted source of master data, reducing duplication, resolving conflicts, and enabling reliable reporting and analytics.

Data collected by entities that do not have a direct relationship with the individuals whose data is being gathered, typically aggregated from multiple sources and sold to other organisations for marketing, analytics, or enrichment purposes. The value and availability of third-party data have declined sharply due to privacy regulations (GDPR, CCPA), browser restrictions on third-party cookies, and growing consumer demand for data transparency.

An automated sequence of data processing steps that extracts, transforms, and loads data from source systems into target systems for analysis, reporting, or machine learning model training. Well-architected data pipelines are critical infrastructure assets that enable data-driven decision-making and AI deployment, and their reliability directly impacts downstream business processes.

Data collected directly by an organisation from its own customers, users, or audience through owned channels such as websites, apps, CRM systems, transactions, and surveys. First-party data is considered the most valuable data category because it is collected with consent, is unique to the organisation, and provides direct insight into customer behaviour and preferences.

The dataset used to train a machine learning model, comprising examples from which the model learns patterns, relationships, and decision boundaries. High-quality, proprietary training data is a significant competitive advantage and intangible asset, particularly in regulated industries where data scarcity creates barriers to entry.

A distributed computing paradigm that processes data near the source of generation rather than in a centralised data centre, reducing latency, bandwidth costs, and data privacy risks. Edge computing is essential for real-time AI applications such as autonomous vehicles, industrial IoT, and point-of-sale analytics.

The EU regulatory framework for insurance and reinsurance companies, establishing risk-based capital requirements, governance standards, and supervisory reporting obligations. Solvency II uses a three-pillar structure: quantitative requirements (Pillar 1), governance and risk management (Pillar 2), and disclosure and transparency (Pillar 3).

Data as a Balance Sheet Asset: Valuation Methods for the AI Era

Data is now formally recognised as productive capital by the System of National Accounts. But how do you value it on a balance sheet? Tony Hillier draws on 30 years of structured finance experience to map three valuation approaches — and where data assets fit into modern capital structures.

How do you create and manage a portfolio of companies in Opagio?

Opagio's portfolio feature lets investors and fund managers add multiple companies, track their intangible asset values over time, compare benchmarks, and generate consolidated portfolio-level reports.

What AI governance frameworks should companies adopt?

Companies should adopt AI governance frameworks covering ethical principles, risk management, transparency, accountability, and compliance — drawing from standards like the EU AI Act, NIST AI RMF, and ISO/IEC 42001.

What does AI due diligence involve for investors?

AI due diligence evaluates a company's AI capabilities, data assets, model performance, technical debt, governance practices, talent dependency, and the defensibility of its AI competitive advantages.