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Datasets & feeds · Scoped dataset pricing

Data Marketplace Pricing for the records you need.

Begin with a relevant collection and representative sample. Pricing follows the entities, markets, fields, history, refresh, and delivery that make the dataset useful to your team.

Data Marketplace pricing at a glance, with the workload inputs used to select a plan or scope the right capacity.
Scoped plan
Price the usable record set

Sample, scope, history, and delivery reviewed

Priced by
Dataset, entity, and market coverage
Evaluate with
Representative production inputs
La prochaine étape
Request a focused quote

Custom pricing

Build the quote from a representative workload.

Custom pricing turns the operating profile into a clear proposal. Share the inputs that affect capacity, execution, delivery, and support so the plan matches production.

Request a quote
  1. 01
    Show the workload

    Bring representative sources, targets, or delivery requirements.

  2. 02
    Make demand visible

    Map volume, cadence, concurrency, coverage, and outputs.

  3. 03
    Align the operating model

    Include quality, support, security, destination, and contracting needs.

  4. 04
    Receive a focused plan

    Review the configuration and commercial scope as one proposal.

Cost drivers

The inputs that shape Data Marketplace pricing.

Use these four inputs to compare plans or prepare a quote with less guesswork and a clearer production fit.

01

Dataset, entity, and market coverage

Select the sources, entities, and markets that define the dataset coverage your team can use.

02

Record volume and selected fields

Compare record count and field depth against the model, analysis, or application consuming the data.

03

Historical depth and refresh requirements

Match freshness and historical depth to the decision window instead of buying unused recency.

04

Format, destination, and usage scope

Choose the delivery format, usage scope, and support path needed for downstream adoption.

Choose your path

Start at the level that matches the decision.

Move from representative evidence to a commercial path without over-sizing the first step.

01

One-time analysis

Select a prepared collection for a defined market, entity, or research question.

02

Custom dataset package

Shape fields, coverage, history, and delivery around a specific model or workflow.

03

Recurring requirement

Move repeated refresh needs into a Data Feed or managed delivery plan.

Pricing FAQ

Data Marketplace pricing questions, answered.

Use these answers to choose the buying path and prepare a representative evaluation or pricing brief.

How is Data Marketplace pricing determined?

Pricing reflects the selected collection, entity and market coverage, record volume, fields, history, refresh needs, format, and delivery.

Can I review sample records first?

Yes. A representative sample helps your team validate fields, coverage, and fit before defining the complete dataset package.

What should I include in a dataset request?

Share the business question, entities, markets, fields, time range, expected record volume, format, and delivery destination.

Is Data Marketplace suited to recurring delivery?

It can support a prepared dataset purchase. When the same scope needs regular refreshes, Data Feeds provides a clearer recurring-delivery path.

Can a dataset be shaped around a model or analytics workflow?

Yes. Define the records, attributes, coverage, history, and output structure needed by the downstream system so the package is scoped around its use.

La prochaine étape

Turn the Data Marketplace workload into a clear plan.

Bring the sources, volume, execution, delivery, and support profile for a focused configuration and quote.