Locate data that is already public
When suitable data already exists, we locate the source and provide the verified links and organized findings.
DATASETS · CUSTOM SERVICE
Custom datasets · Built to requirement, verifiable on delivery
When public sources do not contain a ready-made dataset, or existing data cannot support the research or business task, DeepSData can collect, clean, verify and prepare a dataset against confirmed mandatory requirements. Feasibility review is free; delivery begins only after the route and scope are agreed.
CHOOSING THE RIGHT SERVICE
Search, custom preparation or an existing dataset
These routes address different needs. We first identify the appropriate route so that the work and budget match the actual requirement.
Build what public sources do not provide
When public data is missing or insufficient, we build a new dataset against the confirmed requirements.
Use a dataset already prepared by DeepSData
Previously prepared datasets can be selected where the fields, definitions and permitted use match the new requirement.
SERVICE LEVELS
Assess first, then proceed to delivery
The service can progress from feasibility review to a high-verification custom package. Each stage has a clear output before the next stage begins.
Feasibility review
Determine whether the requirement is feasible, partly feasible or not advisable.
Sample package
Review the quality and definitions before deciding whether to continue.
Standard delivery package
Main data, field dictionary, source notes and README.
High-verification package
Adds source detail, definition notes, sampling checks and version records.
DELIVERY PROCESS
Six steps from requirement to acceptance
1 · Structure the requirement
Confirm the objective, mandatory conditions, preferences and required outputs.
2 · Review feasibility
Check sources, permission boundaries and the practical acquisition route before making a delivery commitment.
3 · Confirm scope and price
Set out the deliverables, exclusions, schedule, price and acceptance criteria.
4 · Collect and prepare
Collect, clean, deduplicate and organize the data against the confirmed conditions.
5 · Verify each condition
Check whether each record meets, partly meets or fails the mandatory conditions.
6 · Deliver and accept
Provide the agreed files and supporting documentation for acceptance.
WHAT THE DELIVERY PROVIDES
Clear sources, fields and acceptance criteria
Traceable sources
Source notes are retained so that the delivered dataset can be reviewed against its stated basis.
Condition-based verification
Records are checked against the confirmed requirements rather than counted as matches on the strength of a title or lead alone.
Defined use boundaries
Permission, privacy and redistribution limits are handled according to the applicable source and agreement.
DELIVERABLES
What you receive
The delivery format is agreed for the project and may include the main data, field dictionary, source notes, README, missing-value and exception notes, version records and agreed scripts or tools.
DataMain files and field definitions
SourcesSource notes at the agreed level
QualityMissing values and exceptions stated clearly
IntegrityDelivery manifest and file checks where agreed
ANONYMIZED EXAMPLE CARDS
Anonymized custom dataset examples
These cards omit client identities and dataset contents. They show the dataset direction and the public documentation available for each example.
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FAQ
Common questions
Can you build a dataset that is not available publicly?
We first review whether the required data can be obtained legally and reliably. If the requirement is not feasible, we will say so and suggest a practical alternative where possible.
How is custom preparation different from dataset search?
Search locates data that already exists. Custom preparation is used when public sources do not provide a dataset that meets the confirmed requirements.
Can we begin with a sample?
Yes. For a large or complex requirement, a sample can be used to confirm fields, definitions and quality before full production.
Can I specify fields and delivery formats?
Yes. Fields, definitions and delivery formats are confirmed before production begins.
How is confidentiality handled?
Client identity and commissioned work are treated as confidential. Public examples are anonymized and do not expose the commissioned dataset itself.
How long does delivery take?
The schedule depends on data availability, scale and verification requirements. A clear schedule is provided after the requirement and route are confirmed.
Tell us what data you need
Start with the research objective, mandatory fields, time and geography, intended use and preferred delivery format.