Learn the business behind the data.
A practical handbook for the questions that come before the deal. Start at the beginning, or go straight to what you need.
How to sell data: from a raw dataset to your first deal
A practical guide to selling a dataset: establish your rights, choose a buyer use case, prepare a sample, price the license, and run a paid pilot.
How to start a data brokerage business
Choose a brokerage model, validate a niche, negotiate supplier permissions, qualify buyers, and build a repeatable data brokerage operation.
How to find buyers for your dataset
Map your data to buyer teams, distinguish marketplaces from buyers, qualify demand, and write an evidence-led data sales pitch.
How to sell data to AI companies
Understand AI data buying: training, evaluation, licensed content, enterprise workflows, and the evidence an AI data partner needs.
How to price a dataset and structure a data deal
Compare dataset pricing models, calculate contribution, define license scope, and use a paid pilot to test willingness to pay.
How to package a dataset buyers can evaluate
Prepare a dataset card, field dictionary, representative sample, quality report, and versioned delivery manifest for a commercial data product.
Data licensing: the terms to settle before a deal
A practical issue checklist for data licenses: permitted uses, training rights, redistribution, exclusivity, updates, deletion, warranties, and payment.
A buyer’s checklist for data due diligence
Evaluate a data vendor’s provenance, rights, coverage, quality, delivery, privacy controls, and commercial fit before buying a dataset.
Anonymizing data before a commercial release
Understand anonymisation, pseudonymisation, contextual identifiers, release review, and why removing names does not establish that a dataset is safe to sell.
Data broker laws: scope the rules before you sell
A starting checklist for data brokerage compliance, including jurisdiction, personal information, California DROP, EU privacy duties, and contractual rights.
How to run a paid data pilot that leads to a decision
Design a data evaluation with a clear use case, sample, acceptance criteria, license scope, timeline, payment, and go/no-go decision.
Selling alternative data: what research buyers need
Prepare alternative data for research buyers with point-in-time history, source methodology, coverage, revision records, and a testable evaluation.
Direct sales, licensing partners, or data marketplaces?
Choose a data sales channel by comparing customer ownership, exclusivity, channel fees, delivery work, and the evidence of real demand.
How to compare data vendors and dataset offers
Compare datasets using task fit, coverage, timestamps, rights, quality, delivery, and total cost. Build a useful shortlist without relying on brand rankings.
No guides match that search.
Try a broader term, or choose “All” to see every category.