Data Clean Room

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.

A secure online repository used in M&A transactions, capital raises, and other due diligence processes to store and share confidential documents with authorised parties. Virtual data rooms provide granular access controls, activity tracking, watermarking, and Q&A workflows.

A software system that creates a unified, persistent customer database accessible to other systems by collecting and integrating customer data from multiple sources — including CRM, website analytics, email, social media, transactions, and customer service interactions. CDPs resolve customer identities across channels and devices to build comprehensive individual profiles, enabling personalised marketing, customer journey orchestration, and advanced segmentation.

Artificially generated data that mimics the statistical properties of real-world datasets, used to train machine learning models when actual data is scarce, sensitive, or expensive to obtain. Synthetic data enables AI development in privacy-constrained domains such as healthcare and finance, while reducing data acquisition costs and regulatory exposure.

A centralised repository that stores large volumes of raw data in its native format — structured, semi-structured, and unstructured — until it is needed for analysis. Unlike data warehouses, which store data in predefined schemas, data lakes use a schema-on-read approach that provides flexibility for diverse analytical workloads including machine learning, real-time analytics, and ad hoc exploration.

Data that a customer intentionally and proactively shares with a business, including preferences, purchase intentions, communication choices, and personal context. Unlike first-party data (which is observed from behaviour), zero-party data is explicitly volunteered through mechanisms such as preference centres, surveys, quizzes, and account settings.

The California Consumer Privacy Act, a US state privacy law granting California residents rights over their personal information, including the right to know what data is collected, the right to delete it, the right to opt out of its sale, and the right to non-discrimination for exercising these rights. As amended by the CPRA (2023), CCPA closely mirrors certain GDPR provisions and has influenced privacy legislation in other US states.

A machine learning technique that trains models across multiple decentralised devices or servers holding local data, without transferring the raw data to a central location. Federated learning addresses data privacy and sovereignty concerns by keeping sensitive data on-device while still enabling collaborative model improvement.

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.