Data broker glossary

A data broker glossary of the terms you meet when companies buy, sell and license data, each explained with a worked example.

Updated

All glossary

PageWhat it coversUpdated
What is DaaS (data as a service)?DaaS, short for data as a service, means a provider keeps data current and customers reach it on demand instead of buying a static file.2026-11-07
What is an AI dataset?An AI dataset is the material a model learns from: what it contains, how it is organised, and what buyers check before licensing one.2026-11-07
Data enrichment: what it meansData enrichment adds context a dataset lacks, from outside sources or from analysis, so it answers more questions than it could alone.2026-11-07

Why a glossary for data deals

The trade in data borrows its vocabulary from marketing, law, finance and machine learning at once, and each field uses the same words a little differently. A marketer hears "first-party data" and thinks of cookies and consent banners. A lawyer hears it and thinks about who collected the information and under which privacy notice. An AI lab hears it and wonders whether the seller can prove where it came from. When a seller and a buyer use one word in two senses, the misunderstanding usually surfaces late, in diligence or in the licence, where it is expensive to fix.

Every entry here starts with a short definition you can quote, then shows the term at work in a realistic dataset deal and sets it beside the words it is most often confused with. Where a term has a legal meaning in a state law, the entry says so and points to the law page. Where an entry mentions a figure, it names the source; the rest is explanation, not data.

Every term, A to Z

Grouped by the stage of a brokered deal where the term usually comes up. Links appear as each entry is published.
TermWhere it comes up
AI datasetMatching: what AI buyers want
Alternative dataMatching: investment buyers
B2B dataSourcing: company and contact data
Consumer dataQualifying: personal data and the law
Data aggregatorSourcing: who combines sources
Data appendValuing: filling gaps in a file
Data as a productSourcing: how sellers organise data
Data as a service (DaaS)Closing: delivery by subscription
Data brokerEvery stage: the role itself
Data clean roomClosing: sharing without handing over
Data commercializationSourcing: bringing data to market
Data enrichmentValuing: adding context to records
Data licensingClosing: the legal instrument
Data marketplaceMatching: platforms that list data
Data monetizationSourcing: why companies sell
Data ownershipQualifying: who may license
Data productValuing: the packaged dataset
First-party dataQualifying: where data came from
Information brokerEvery stage: the older name for the role
Intent dataMatching: sales and marketing buyers
LLM training dataMatching: language model buyers
Second-party dataSourcing: partner data
Third-party dataQualifying: bought-in data
Virtual data roomClosing: diligence and samples
Zero-party dataQualifying: data people chose to share

Terms that travel in groups

  • Zero-, first-, second- and third-party data describe one question from four angles: how far the data has travelled from the people it describes. Read them together.
  • Monetization, commercialization and licensing are often swapped. Monetization is the goal, commercialization is the work of taking data to market, and licensing is the contract that lets someone else use it.
  • Data product and data as a product sound alike but aren't. The first is a thing a buyer can license; the second is a way of running data inside a company.
  • Enrichment and append both add to a file. Append fills named gaps by matching; enrichment is the wider job of adding context.
  • Data broker, information broker and data aggregator overlap heavily. Each entry says where the lines usually fall, and the law pages show where a statute draws them.

How the entries are written

Examples are illustrations, written to show how a term behaves in a deal, not reports of real transactions. Definitions are our own wording. Legal points describe the law in general and say when to ask a lawyer. Each page shows the date it last changed and lists the sources behind any factual claim with the date they were checked.

Questions people ask

What is the difference between a data broker and an information broker?

In everyday use they overlap. Information broker is the older term, often for researchers who find information on request; data broker is the term state laws now use for businesses that sell personal data about people they don't deal with directly.

Which terms matter most to someone new to brokering datasets?

Start with data broker, data licensing, data ownership and first-party data. Together they cover what you do, the contract you use, who may sign it and where the data came from.

Are these definitions legal definitions?

No. They explain how the words are used in practice. Where a state law gives a term a specific meaning, such as data broker, the entry links to the law page, and the statute's wording is what counts.

Related

Become a data broker

The DataBroker course and tools: find companies with data to sell, price it, license it and close the deal.