Connect S3 datasets to Uplyst
Amazon S3 stores objects in buckets, supporting data lakes, application exports and enterprise archives. Uplyst connects approved datasets with its intelligence layer, linking stored records to customers, suppliers, assets and transactions.
The integration scope identifies the buckets, object prefixes, file formats and business datasets involved. Related files can be treated as one delivery when they represent a common reporting period or operational process.
settlement/2026-09-25/| Manifest member | Records | Control total |
|---|---|---|
part-01.csvVersion Qx8mkP1nr7Validated | Records800 | Control total£248,600.00 |
part-02.csvVersion Rj9vnT3aw2Validated | Records800 | Control total£251,400.00 |
part-03.csvRequired version Lp2bcN6ks4Not received | Expected records400 | Expected total£125,000.00 |
- Manifest
- 3 members2,000 records · £625,000.00
- Validated delivery
- 2 members1,600 records · £500,000.00
The declared third member and its control total must reconcile before the delivery enters settlement analysis.
The delivery contract defines membership and validation. An S3 notification alone does not establish a complete dataset.
Bucket access and workload permissions
IAM policies, bucket policies and access points control access to S3 resources. The connection is limited to the objects and operations required for the selected datasets.
Encryption settings and cross-account access may introduce additional permissions. These are part of the source configuration alongside the bucket location and workload identity.
Object updates and notifications
S3 event notifications can signal changes such as object creation. Notifications may repeat or arrive out of order, so an event is a signal to inspect an object rather than proof that a complete business dataset is available.
Object keys and version IDs, where versioning is enabled, identify the source data behind an update. These references help distinguish a new file from a replacement or repeated delivery.
File data with business meaning
A stored file becomes useful when its fields are connected to business entities, dates, currencies and operational states. Uplyst's semantic model brings that meaning together with information from other enterprise systems.
Dataset checks can include required fields, reporting periods and control totals. The chosen checks depend on the source format and the business process using the data.
Reconciliation and reporting
S3 exports are useful for financial reconciliation, inventory analysis and reporting across systems. Linking them with live operational records gives teams a way to investigate differences and follow them back to the source.
Delivery schedules and source references also help identify missing or corrected datasets before they affect downstream analysis.