Are the Logistics and supply chain records on this page real?

No. Every record on this page is synthetic, generated from a fixed seed by the pack's own generator; masked values come from the real masking engine. The masking example uses a fixed public sample key; your own data is masked with a key from your secret store.

How long does a first certified Logistics and supply chain dataset take?

Estimates, not guarantees — try the synthetic sandbox: minutes; install (or reuse) the agent: under an hour; connect a source: under an hour; review and approve policies: under an hour; first certified dataset: minutes.

Which test scenarios does the Logistics and supply chain pack include?

11 runnable scenarios (everyday parcels, customs holds, failed deliveries, returns to sender and more), plus 1 negative-test scenario kept apart from valid data.

Do Logistics and supply chain rows leave my network?

No. The DataNivra agent runs inside your environment: it reads the source, masks, subsets, generates and certifies there, and sends only metadata, aggregate counts and evidence to the DataNivra control plane (customer-resident processing, zero raw-production-data egress).

Industry packs

Logistics and supply chain industry pack

Synthetic shipment, parcel, tracking, customs and freight test data with linked masking

Preview only · not activatable yet Version 1.0.0 · Complete

Try with synthetic data Notify me — tell us you need it

Everything on this page works without an account. Prefer a conversation? Request a demo (optional). Missing something? Request a feature.

This pack is installed and passes DataNivra’s pack conformance kit through the real engine, but it cannot be activated yet: no plan includes it yet, the standard agent image does not ship it, the control-plane catalogue does not list it and the hosted sandbox has no synthetic estate for it. You can explore its synthetic records, masking and scenarios on this page and in the browser demo. Tell us if you need it: demand decides which packs become activatable next.

Problems this pack solves

Masked data that still joins across 5 systems

7 cross-system relationships link billing, carrier, customs, tms and wms; the pack's masking keeps one pseudonym per identity on every side. For example, tms.shippers.shipper_id and billing.freight_invoices.shipper_ref get the same pseudonym.

The cases production samples rarely contain

9 ready-made scenarios generate them on demand, for example: international shipments whose customs declarations are held or inspected, with a reason; failed delivery attempts and refusals at the door, without a signature; undeliverable shipments returned to the shipper and booked back into the warehouse.

Sensitive fields found and masked before anyone sees them

43 columns across 13 entities are classified (direct identifier, financial, PII, quasi identifier and sensitive) and covered by 3 masking templates you review and approve.

Evidence that each dataset is fit to use

2 certification presets check masking coverage, referential integrity, orphans and row counts before a dataset can be provisioned; a failed dataset is never provisioned.

Entities and relationships

13 entities across 5 source systems, generated from the pack’s own entity model.

Arrows point from the referencing entity to the one it references. Solid: a foreign key inside one system. Dashed: a cross-system relationship — the pack keeps the same pseudonym on both sides, so masked data still joins.

All 16 relationships as a table

Relationships of the Logistics and supply chain pack
Entity	References	Columns	Kind
Shipment	Shipper	`shipper_id` → `shipper_id`	Within a system
Shipment	Consignee	`consignee_id` → `consignee_id`	Within a system
Parcel	Shipment	`shipment_id` → `shipment_id`	Within a system
StockMovement	Warehouse	`warehouse_code` → `warehouse_code`	Within a system
Vehicle	Carrier	`carrier_code` → `carrier_code`	Within a system
Driver	Carrier	`carrier_code` → `carrier_code`	Within a system
TrackingEvent	Driver	`driver_id` → `driver_id`	Within a system
TrackingEvent	Vehicle	`vehicle_id` → `vehicle_id`	Within a system
ProofOfDelivery	Driver	`driver_id` → `driver_id`	Within a system
Shipment	Carrier	`carrier_ref` → `carrier_code`	Across systems (pack relationship template)
StockMovement	Shipment	`shipment_ref` → `shipment_id`	Across systems (pack relationship template)
TrackingEvent	Parcel	`tracking_ref` → `tracking_number`	Across systems (pack relationship template)
ProofOfDelivery	Parcel	`tracking_ref` → `tracking_number`	Across systems (pack relationship template)
CustomsDeclaration	Shipment	`shipment_ref` → `shipment_id`	Across systems (pack relationship template)
FreightInvoice	Shipper	`shipper_ref` → `shipper_id`	Across systems (pack relationship template)
FreightInvoice	Shipment	`shipment_ref` → `shipment_id`	Across systems (pack relationship template)

Realistic synthetic records

Synthetic data. Every record on this page is synthetic, generated from a fixed seed by the pack's own generator; masked values come from the real masking engine.

Entity

Shipper — `tms.shippers` (synthetic)
`shipper_id` sensitive	`company_name`	`contact_name` sensitive	`contact_email` sensitive	`contact_phone` sensitive	`tax_id` sensitive	`country_code`	`account_tier`
SHP00000001	Ivervane Trading	Iro Morby	—	555-063-4648	VAT-ZZ-57908886	ZZ	STANDARD
SHP00000002	Ashford Trading	Joan Dunmere	joan.pemford9160@example.net	555-060-0991	VAT-ZZ-95585808	ZZ	PREFERRED

Masking: before and after

Template Linked logistics test data (LOG_LINKED_TEST_DATA) applied to a synthetic Shipper record from tms.shippers.

Synthetic record

Synthetic Shipper record before and after masking
Column	Classified as	Before (synthetic)	After masking
`shipper_id`	Direct identifier	`SHP00000001`	`SHP16473359`
`contact_name`	PII, Direct identifier	`Iro Morby`	`Orel Langridge`
`contact_email`	PII, Direct identifier	`—`	`—` (same value after masking)
`contact_phone`	PII, Direct identifier	`555-063-4648`	`555-033-2654`
`tax_id`	PII, Direct identifier	`VAT-ZZ-57908886`	`IZP-OJ-26647919`

Same pseudonym in two systems. The identifier SHP00000001 appears in tms.shippers.shipper_id and in billing.freight_invoices.shipper_ref. Both become SHP16473359, so the masked systems still join (relationship LOG_INVOICE_SHIPPER).

Masked with a fixed public sample key so this example is reproducible; your data is masked with your own key, referenced from your secret store.

Synthetic scenarios you can run

11 runnable scenarios. Preview them in your browser without an account; the hosted sandbox opens when the pack becomes activatable.

Everyday parcels

Normal LOG_EVERYDAY_PARCELS

Ordinary shippers, consignees, shipments, parcels, warehouse movements, scans and invoices

Everyday, valid records: the baseline most tests expect. Children per parent record: 1–3.

Preview in the browser demo: Everyday parcels

Customs holds

Rare LOG_CUSTOMS_HOLDS

International shipments whose customs declarations are held or inspected, with a reason

Valid but uncommon business situations that production samples often miss. Children per parent record: 1–2.

Preview in the browser demo: Customs holds

Failed deliveries

Rare LOG_FAILED_DELIVERIES

Failed delivery attempts and refusals at the door, without a signature

Valid but uncommon business situations that production samples often miss. Children per parent record: 1–3.

Preview in the browser demo: Failed deliveries

Returns to sender

Rare LOG_RETURNS_TO_SENDER

Undeliverable shipments returned to the shipper and booked back into the warehouse

Valid but uncommon business situations that production samples often miss. Children per parent record: 1–2.

Preview in the browser demo: Returns to sender

Lost parcels

Rare LOG_LOST_PARCELS

Shipments lost in the network after a hub scan; their invoices are disputed

Valid but uncommon business situations that production samples often miss. Children per parent record: 1–2.

Preview in the browser demo: Lost parcels

Hazmat parcels

Rare LOG_HAZMAT_PARCELS

Dangerous-goods parcels carrying an invented hazard class, never on same-day service

Valid but uncommon business situations that production samples often miss. Children per parent record: 1–3.

Preview in the browser demo: Hazmat parcels

Peak season surge

Rare LOG_PEAK_SEASON_SURGE

A burst of carrier scans and deliveries within three peak-season days

Valid but uncommon business situations that production samples often miss. Children per parent record: 3–8.

Preview in the browser demo: Peak season surge

Heavy parcel threshold

Boundary LOG_HEAVY_PARCEL_THRESHOLD

Parcel weights exactly at the two-person handling limit or ten grams either side of it

Values at the edges of valid ranges (limits, thresholds, extremes). Children per parent record: 1–3.

Preview in the browser demo: Heavy parcel threshold

Sla cutoff deliveries

Boundary LOG_SLA_CUTOFF_DELIVERIES

Deliveries exactly at the promised time or one minute either side of it

Values at the edges of valid ranges (limits, thresholds, extremes). Children per parent record: 1–2.

Preview in the browser demo: Sla cutoff deliveries

Duplicate scans

Duplicate LOG_DUPLICATE_SCANS

Carrier scans delivered twice by an integration with identical content under new ids

Records that repeat others under new keys (clean-up and matching tests). Children per parent record: 2–5.

Preview in the browser demo: Duplicate scans

Shipment histories

Historical LOG_SHIPMENT_HISTORIES

Multi-year, referentially intact shipment, tracking, customs and billing histories

Old records for archive, migration and retention tests. Children per parent record: 2–4.

Preview in the browser demo: Shipment histories

Negative tests, kept apart. This scenario produces deliberately broken data for error handling and never passes certification as valid data:

LOG_BROKEN_REFERENCES — Dangling cross-system references and invalid values for error-handling tests

Sample schemas and representative outputs

The schema the pack expects in each system (also as CREATE TABLE DDL in the downloads). A run produces a masked or synthetic dataset with the same tables, a certification report with the gates of the chosen preset, and an evidence manifest with checksums — the rows stay in your environment.

Shipper — tms.shippers · 8 columns

A shipper account (the natural subset root): a business or sole trader sending goods.

Column	Type	Required	Sensitive classes
`shipper_id` (key)	`VARCHAR(12)`	Yes	Direct identifier
`company_name`	`VARCHAR(64)`	Yes	—
`contact_name`	`VARCHAR(128)`	Yes	PII, Direct identifier
`contact_email`	`VARCHAR(128)`	No	PII, Direct identifier
`contact_phone`	`VARCHAR(32)`	No	PII, Direct identifier
`tax_id`	`VARCHAR(20)`	No	PII, Direct identifier
`country_code`	`VARCHAR(2)`	Yes	—
`account_tier`	`VARCHAR(12)`	Yes	—

Consignee — tms.consignees · 10 columns

The person or business a shipment is delivered to.

Column	Type	Required	Sensitive classes
`consignee_id` (key)	`BIGINT`	Yes	—
`full_name`	`VARCHAR(128)`	Yes	PII, Direct identifier
`email`	`VARCHAR(128)`	No	PII, Direct identifier
`phone`	`VARCHAR(32)`	No	PII, Direct identifier
`street_address`	`VARCHAR(128)`	Yes	PII, Quasi identifier
`city`	`VARCHAR(64)`	Yes	Quasi identifier
`postal_code`	`VARCHAR(10)`	No	PII, Quasi identifier
`country_code`	`VARCHAR(2)`	Yes	—
`delivery_instructions`	`VARCHAR(300)`	No	Sensitive
`is_business`	`BOOLEAN`	Yes	—

Shipment — tms.shipments · 12 columns

A booked consignment from a shipper to a consignee, handed to one carrier.

Column	Type	Required	Sensitive classes
`shipment_id` (key)	`VARCHAR(14)`	Yes	Direct identifier
`shipper_id`	`VARCHAR(12)`	Yes	Direct identifier
`consignee_id`	`BIGINT`	Yes	—
`carrier_ref`	`VARCHAR(8)`	Yes	—
`service_level`	`VARCHAR(10)`	Yes	—
`payment_terms`	`VARCHAR(14)`	Yes	—
`declared_value`	`DECIMAL(12,2)`	Yes	Financial
`is_international`	`BOOLEAN`	Yes	—
`created_at`	`TIMESTAMP`	Yes	—
`promised_by`	`TIMESTAMP`	Yes	—
`actual_delivery_at`	`TIMESTAMP`	No	—
`status`	`VARCHAR(10)`	Yes	—

Parcel — tms.parcels · 8 columns

One labelled piece of a shipment, identified by its tracking number.

Column	Type	Required	Sensitive classes
`tracking_number` (key)	`VARCHAR(16)`	Yes	Direct identifier
`shipment_id`	`VARCHAR(14)`	Yes	Direct identifier
`weight_kg`	`DECIMAL(7,2)`	Yes	—
`length_cm`	`INT`	Yes	—
`width_cm`	`INT`	Yes	—
`height_cm`	`INT`	Yes	—
`is_hazmat`	`BOOLEAN`	Yes	—
`hazmat_class`	`VARCHAR(8)`	No	—

Warehouse — wms.warehouses · 4 columns

A fulfilment warehouse (a facility, not a person).

Column	Type	Required	Sensitive classes
`warehouse_code` (key)	`VARCHAR(8)`	Yes	—
`region_code`	`VARCHAR(8)`	Yes	—
`capacity_pallets`	`INT`	Yes	—
`is_bonded`	`BOOLEAN`	Yes	—

StockMovement — wms.stock_movements · 8 columns

A warehouse movement (inbound, pick, pack, outbound, return) for a shipment.

Column	Type	Required	Sensitive classes
`movement_id` (key)	`BIGINT`	Yes	—
`warehouse_code`	`VARCHAR(8)`	Yes	—
`shipment_ref`	`VARCHAR(14)`	Yes	Direct identifier
`sku`	`VARCHAR(16)`	Yes	—
`quantity`	`INT`	Yes	—
`movement_type`	`VARCHAR(10)`	Yes	—
`bin_location`	`VARCHAR(12)`	Yes	—
`moved_at`	`TIMESTAMP`	Yes	—

Carrier — carrier.carriers · 4 columns

A road or air carrier (an organisation; its code is an unmasked business key).

Column	Type	Required	Sensitive classes
`carrier_code` (key)	`VARCHAR(8)`	Yes	—
`name`	`VARCHAR(64)`	Yes	—
`mode`	`VARCHAR(6)`	Yes	—
`is_subcontractor`	`BOOLEAN`	Yes	—

Vehicle — carrier.vehicles · 5 columns

A delivery vehicle; its plate links a driver and a route to a place and time.

Column	Type	Required	Sensitive classes
`vehicle_id` (key)	`BIGINT`	Yes	—
`carrier_code`	`VARCHAR(8)`	Yes	—
`registration_plate`	`VARCHAR(12)`	Yes	Direct identifier
`vehicle_type`	`VARCHAR(10)`	Yes	—
`capacity_kg`	`INT`	Yes	—

Driver — carrier.drivers · 7 columns

A delivery driver (employee or contractor).

Column	Type	Required	Sensitive classes
`driver_id` (key)	`VARCHAR(10)`	Yes	Direct identifier
`carrier_code`	`VARCHAR(8)`	Yes	—
`full_name`	`VARCHAR(128)`	Yes	PII, Direct identifier
`phone`	`VARCHAR(32)`	No	PII, Direct identifier
`licence_number`	`VARCHAR(16)`	No	PII, Direct identifier
`birth_date`	`DATE`	No	PII, Quasi identifier
`employment_type`	`VARCHAR(10)`	Yes	—

TrackingEvent — carrier.tracking_events · 8 columns

A scan of a parcel (location-like: where and when the parcel — and its consignee — was).

Column	Type	Required	Sensitive classes
`event_id` (key)	`BIGINT`	Yes	—
`tracking_ref`	`VARCHAR(16)`	Yes	Direct identifier
`event_code`	`VARCHAR(20)`	Yes	—
`occurred_at`	`TIMESTAMP`	Yes	Quasi identifier
`grid_cell`	`VARCHAR(10)`	Yes	Quasi identifier
`hub_code`	`VARCHAR(8)`	No	—
`driver_id`	`VARCHAR(10)`	No	Direct identifier
`vehicle_id`	`BIGINT`	No	—

ProofOfDelivery — carrier.proofs_of_delivery · 9 columns

The outcome of a delivery attempt with recipient, signature and photo references.

Column	Type	Required	Sensitive classes
`pod_id` (key)	`BIGINT`	Yes	—
`tracking_ref`	`VARCHAR(16)`	Yes	Direct identifier
`driver_id`	`VARCHAR(10)`	Yes	Direct identifier
`delivered_at`	`TIMESTAMP`	Yes	Quasi identifier
`outcome`	`VARCHAR(20)`	Yes	—
`recipient_name`	`VARCHAR(128)`	No	PII, Direct identifier
`signature_ref`	`VARCHAR(24)`	No	Direct identifier
`photo_ref`	`VARCHAR(24)`	No	Direct identifier
`grid_cell`	`VARCHAR(10)`	Yes	Quasi identifier

CustomsDeclaration — customs.declarations · 9 columns

An export/import declaration of an international shipment.

Column	Type	Required	Sensitive classes
`declaration_id` (key)	`BIGINT`	Yes	—
`shipment_ref`	`VARCHAR(14)`	Yes	Direct identifier
`declarant_tax_id`	`VARCHAR(20)`	No	PII, Direct identifier
`commodity_code`	`VARCHAR(10)`	Yes	—
`declared_value`	`DECIMAL(12,2)`	Yes	Financial
`origin_country`	`VARCHAR(2)`	Yes	—
`status`	`VARCHAR(10)`	Yes	—
`hold_reason`	`VARCHAR(20)`	No	—
`lodged_at`	`TIMESTAMP`	Yes	—

FreightInvoice — billing.freight_invoices · 9 columns

A freight charge invoiced to the shipper for one shipment.

Column	Type	Required	Sensitive classes
`invoice_id` (key)	`BIGINT`	Yes	—
`shipper_ref`	`VARCHAR(12)`	Yes	Direct identifier
`shipment_ref`	`VARCHAR(14)`	Yes	Direct identifier
`amount`	`DECIMAL(10,2)`	Yes	Financial
`currency`	`VARCHAR(3)`	Yes	—
`issued_on`	`DATE`	Yes	—
`status`	`VARCHAR(10)`	Yes	—
`payer_iban`	`VARCHAR(34)`	No	Financial, Direct identifier
`payment_reference`	`VARCHAR(20)`	No	Financial, Direct identifier

Compatible connectors

Verified with this pack version: PostgreSQL and Local files (Parquet / CSV). 17 more connectors are compatible by capability: they support what the pack needs, but have not been verified with this pack yet.

Connector	Status with Logistics and supply chain
Local files (Parquet / CSV)	Verified with this pack
PostgreSQL	Verified with this pack
Amazon S3 / S3-compatible storage	Compatible by capability (not yet verified with this pack)
Apache Kafka (connector in preview)	Compatible by capability (not yet verified with this pack)
Azure Blob Storage / Data Lake Storage	Compatible by capability (not yet verified with this pack)
Databricks	Compatible by capability (not yet verified with this pack)
Generic SQL (SQLAlchemy)	Compatible by capability (not yet verified with this pack)
Google BigQuery	Compatible by capability (not yet verified with this pack)
HTTP APIs (connector in preview)	Compatible by capability (not yet verified with this pack)
IBM Db2 (connector in preview)	Compatible by capability (not yet verified with this pack)
Mainframe files (EBCDIC / copybook) (connector in preview)	Compatible by capability (not yet verified with this pack)
MariaDB	Compatible by capability (not yet verified with this pack)
Microsoft SQL Server	Compatible by capability (not yet verified with this pack)
MongoDB (connector in preview)	Compatible by capability (not yet verified with this pack)
MySQL	Compatible by capability (not yet verified with this pack)
Oracle Database	Compatible by capability (not yet verified with this pack)
Parquet files	Compatible by capability (not yet verified with this pack)
Snowflake	Compatible by capability (not yet verified with this pack)
SQLite (developer evaluation) (connector in preview)	Compatible by capability (not yet verified with this pack)

Prerequisites and expected setup effort

You need

This pack is not in any plan yet.
One DataNivra agent inside your network (outbound HTTPS only) that ships Logistics and supply chain 1.0.0.
Read-only access to a compatible source (verified with this pack: PostgreSQL, Local files (Parquet / CSV)).
A non-production target environment the agent may write test data to.
A masking key in your own secret store, referenced as vault://…, azure-kv://… or env://… (DataNivra only ever sees the reference).
For production sources, a second person who approves policies (separation of duties).

A DataNivra agent that reports its installed industry packs (releases after agent 0.3.0); the control plane runs a pack job only on an agent holding the exact active pack version with the catalogued integrity digest.

Expected setup effort (estimates)

Step	Estimate
Try the synthetic sandbox No install: sign up and open the sandbox.	Minutes (estimate)
Install (or reuse) the agent One Docker command or a Helm chart; outbound HTTPS only.	Under an hour (estimate)
Connect a source Register a read-only source through the existing connector workflow.	Under an hour (estimate)
Review and approve policies Create drafts from the Logistics and supply chain templates, review and approve them.	Under an hour (estimate)
First certified dataset Run the first job; certification and evidence are produced automatically.	Minutes (estimate)

Certification presets in plain language

`LOG_STRICT`

Every gate; full masking coverage; zero orphaned shipments, parcels, warehouse movements, scans, proofs of delivery, declarations or invoices; exact row counts. Default for masked logistics test data.

Masking coverage of at least 100% of sensitive columns
No orphaned child records
Empty-value ratio may rise by at most 5%
Row counts must match exactly

16 gates it requires

POLICY_COVERAGE: every sensitive column is covered by an approved policy
MASKING_COMPLETION: masking finished on every covered column
REFERENTIAL_INTEGRITY: every reference still points at an existing record
SCHEMA_VALIDATION: the output schema matches the source schema
DATA_QUALITY: empty-value ratios stay within the preset’s drift limit
ROW_COUNT_RECONCILIATION: row counts match the plan within the tolerance
ORPHAN_DETECTION: no child record lost its parent
PROVENANCE: every row is tagged masked or synthetic
MANIFEST: a manifest lists every output table with checksums
POLICY_VERSION: the exact approved policy versions are recorded
ENGINE_VERSION: the engine version is recorded
CHECKSUMS: output checksums are recorded for later verification
IDENTITY_CONSISTENCY: linked identifiers got the same pseudonym in every system
SOURCE_READ_ONLY: the source was only read, never written
EGRESS_GUARD: no row-level data left the agent
CONNECTOR_HEALTH: the connectors stayed healthy during the run

`LOG_SCENARIO_TESTING`

Every gate, with slightly relaxed NULL-ratio drift for scenario datasets whose business states (undelivered shipments, failed attempts without signatures, cleared declarations without a hold reason) leave optional fields empty.

Masking coverage of at least 100% of sensitive columns
No orphaned child records
Empty-value ratio may rise by at most 15%
Row counts must match exactly

16 gates it requires

POLICY_COVERAGE: every sensitive column is covered by an approved policy
MASKING_COMPLETION: masking finished on every covered column
REFERENTIAL_INTEGRITY: every reference still points at an existing record
SCHEMA_VALIDATION: the output schema matches the source schema
DATA_QUALITY: empty-value ratios stay within the preset’s drift limit
ROW_COUNT_RECONCILIATION: row counts match the plan within the tolerance
ORPHAN_DETECTION: no child record lost its parent
PROVENANCE: every row is tagged masked or synthetic
MANIFEST: a manifest lists every output table with checksums
POLICY_VERSION: the exact approved policy versions are recorded
ENGINE_VERSION: the engine version is recorded
CHECKSUMS: output checksums are recorded for later verification
IDENTITY_CONSISTENCY: linked identifiers got the same pseudonym in every system
SOURCE_READ_ONLY: the source was only read, never written
EGRESS_GUARD: no row-level data left the agent
CONNECTOR_HEALTH: the connectors stayed healthy during the run

Activation status

What is missing before you can activate the Logistics and supply chain pack yourself:

no plan includes it yet
the standard agent image does not ship it
the control-plane catalogue does not list it
the hosted sandbox has no synthetic estate for it

Until then, preview it in the browser demo and download its synthetic asset bundle below.

Tell us you need the Logistics and supply chain pack or request a feature for it.

Downloads

Version 1.0.0, 71 files (272.1 KB), all synthetic and generated from the pack itself. Every file’s SHA-256 is listed in MANIFEST.json.

Start here (2)

QUICKSTART.md 3.0 KB · SHA-256 0c2b1b4db18a…
TROUBLESHOOTING.md 4.7 KB · SHA-256 9f65c206fae2…

Entity–relationship diagram (2)

er-diagram.mmd 5.3 KB · SHA-256 326009858303…
er-diagram.svg 9.5 KB · SHA-256 8452a46e0693…

Sample schemas (6)

schema/billing.sql 942 B · SHA-256 e103f43575cc…
schema/carrier.sql 3.1 KB · SHA-256 df75a65d3a1c…
schema/customs.sql 889 B · SHA-256 aee095ed27ac…
schema/entities.json 33.3 KB · SHA-256 1a2d7e0239a2…
schema/tms.sql 2.9 KB · SHA-256 100c4c594e60…
schema/wms.sql 1.1 KB · SHA-256 3ff69dc9822b…

Policy templates (9)

policies/LOG_ANALYTICS_UNLINKED.json 16.8 KB · SHA-256 fceacd3922cd…
policies/LOG_CLASSIFICATION.json 203 B · SHA-256 44d2c0640d2b…
policies/LOG_LINKED_TEST_DATA.json 18.7 KB · SHA-256 9094b9d2622f…
policies/LOG_LOCATION_MINIMISED.json 18.5 KB · SHA-256 f384180a06af…
policies/LOG_REFRESH_WEEKLY.json 190 B · SHA-256 e54930bed540…
policies/LOG_SCENARIO_TESTING.json 549 B · SHA-256 a0728ad1a443…
policies/LOG_STRICT.json 549 B · SHA-256 df479db4f4bb…
policies/LOG_SUBSET_DEFAULT.json 112 B · SHA-256 d46c49c10d7c…
policies/README.md 1.3 KB · SHA-256 342f8f919b47…

API, CLI, SDK and CI/CD examples (10)

api/curl.sh 2.6 KB · SHA-256 0004a02b07cc…
api/dataset-request.json 1.6 KB · SHA-256 10aa2d86540b…
api/policy-approval.json 155 B · SHA-256 d55e632a5036…
api/policy-drafts.json 162 B · SHA-256 1e25229c4597…
api/provision.json 63 B · SHA-256 7f02a6a87792…
api/sandbox.json 50 B · SHA-256 854357bbdc74…
ci/README.md 513 B · SHA-256 7e84ffc245b1…
ci/github-actions.yml 1.9 KB · SHA-256 7b4cb8d682c5…
cli.md 1.8 KB · SHA-256 d9d53a5b712b…
sdk_example.py 1.6 KB · SHA-256 f256c0609b31…

Synthetic sample data (CSV, JSON, Parquet) (40)

synthetic/SYNTHETIC_MANIFEST.json 2.8 KB · SHA-256 935e7bb68427…
synthetic/billing.freight_invoices.csv 1.1 KB · SHA-256 de37511af8eb…
synthetic/billing.freight_invoices.json 3.6 KB · SHA-256 d16589ce0447…
synthetic/billing.freight_invoices.parquet 3.4 KB · SHA-256 ff5fdffade6d…
synthetic/carrier.carriers.csv 231 B · SHA-256 ca4a8a4c99d5…
synthetic/carrier.carriers.json 623 B · SHA-256 a9bc559b3dc9…
synthetic/carrier.carriers.parquet 1.5 KB · SHA-256 577235339d8b…
synthetic/carrier.drivers.csv 1.2 KB · SHA-256 634145699dc3…
synthetic/carrier.drivers.json 3.2 KB · SHA-256 0b1b6660271f…
synthetic/carrier.drivers.parquet 3.0 KB · SHA-256 c7722822f134…
synthetic/carrier.proofs_of_delivery.csv 2.3 KB · SHA-256 8b990a231979…
synthetic/carrier.proofs_of_delivery.json 6.6 KB · SHA-256 fcd38ca8cabc…
synthetic/carrier.proofs_of_delivery.parquet 4.0 KB · SHA-256 92560ed9fdac…
synthetic/carrier.tracking_events.csv 9.5 KB · SHA-256 2c6c36b6bc00…
synthetic/carrier.tracking_events.json 32.3 KB · SHA-256 95ae84f5e14e…
synthetic/carrier.tracking_events.parquet 5.5 KB · SHA-256 f4ab2638ad51…
synthetic/carrier.vehicles.csv 470 B · SHA-256 5102a250b625…
synthetic/carrier.vehicles.json 1.8 KB · SHA-256 83a2e861d231…
synthetic/carrier.vehicles.parquet 2.0 KB · SHA-256 b8a72d08c956…
synthetic/customs.declarations.csv 499 B · SHA-256 4d012fff9151…
synthetic/customs.declarations.json 1.3 KB · SHA-256 00dcc6c76af8…
synthetic/customs.declarations.parquet 3.2 KB · SHA-256 6d063c21c892…
synthetic/tms.consignees.csv 1.6 KB · SHA-256 a9257494140a…
synthetic/tms.consignees.json 4.4 KB · SHA-256 5c195e631e61…
synthetic/tms.consignees.parquet 4.6 KB · SHA-256 6e5e61f89400…
synthetic/tms.parcels.csv 1.8 KB · SHA-256 4183d678cb73…
synthetic/tms.parcels.json 7.1 KB · SHA-256 ebf94472b25d…
synthetic/tms.parcels.parquet 3.2 KB · SHA-256 21ef66adbff7…
synthetic/tms.shipments.csv 2.0 KB · SHA-256 f941f710be02…
synthetic/tms.shipments.json 5.7 KB · SHA-256 8cab51e73f31…
synthetic/tms.shipments.parquet 4.4 KB · SHA-256 47bb9205a29b…
synthetic/tms.shippers.csv 697 B · SHA-256 37ba33225d44…
synthetic/tms.shippers.json 1.6 KB · SHA-256 9d3b06382bd0…
synthetic/tms.shippers.parquet 3.1 KB · SHA-256 2da292e48b90…
synthetic/wms.stock_movements.csv 1.1 KB · SHA-256 a5b4c921555d…
synthetic/wms.stock_movements.json 3.3 KB · SHA-256 e2dc5c273860…
synthetic/wms.stock_movements.parquet 2.9 KB · SHA-256 beae4c1e8fbe…
synthetic/wms.warehouses.csv 213 B · SHA-256 01684b5cc8e4…
synthetic/wms.warehouses.json 639 B · SHA-256 f294a8fef6e6…
synthetic/wms.warehouses.parquet 1.5 KB · SHA-256 28e5f88508dd…

Troubleshooting

The reason codes you can meet on the way, with the recovery step. Every code is also in the error-code catalog.

SANDBOX_PACK_NOT_OFFERED — Synthetic estate not offered: A requested synthetic estate (industry pack) is not available in the hosted sandbox. What to do: Start the sandbox with the default estates.
ENTITLEMENT_REQUIRED — Plan does not include this: Your plan does not include this feature or industry pack. What to do: Upgrade in Billing & Plan.
PACK_INTEGRITY_UNVERIFIED — Pack integrity not verified: This pack version was registered without an integrity digest, so it cannot be activated (fail closed). What to do: Ask your operator to re-register the pack catalogue with the current control-plane image (register-pack), then activate again.
PACK_DEPENDENCY_INACTIVE — Required pack not active: This pack depends on another industry pack that is not active for your organization. What to do: Activate the packs this pack depends on first, then activate it again.
AGENT_PACK_MISSING — No agent can run this industry pack: The job's agent does not report the pack (older agents report no packs at all), so the job was not sent. What to do: Upgrade the agent to a release that reports its installed packs and ships this pack, then run the request again.
AGENT_PACK_VERSION_INCOMPATIBLE — Industry pack version differs on the agent: The agent holds a different version of the pack than the one the job was approved for. What to do: Deploy an agent with the pack's active version, or roll the pack back in Industry packs.
AGENT_PACK_INTEGRITY_MISMATCH — Agent pack differs from the catalogue: The agent reports the pack's version with a different integrity digest than the catalogued one, so the job was not sent. What to do: Redeploy the agent from the official signed image for this release, then run the request again.
PACK_TEMPLATES_UNAVAILABLE — Pack templates not registered: This pack version was registered without its policy templates. What to do: Ask your operator to re-register the pack catalogue (register-pack); create policies manually meanwhile.
PACK_TEMPLATE_KEY_REF_REQUIRED — Masking key reference required: A selected template keeps identities linked across systems and needs your masking key reference. What to do: Provide key_ref, e.g. vault://your-vault/tdm-masking-key, then create the drafts again.
PACK_NOT_ENABLED — Industry pack not enabled: The industry pack is not enabled for this tenant. What to do: Enable the pack (if your plan includes it).

Frequently asked questions

Are the Logistics and supply chain records on this page real?: No. Every record on this page is synthetic, generated from a fixed seed by the pack's own generator; masked values come from the real masking engine. The masking example uses a fixed public sample key; your own data is masked with a key from your secret store.
Can I activate the Logistics and supply chain pack myself?: This pack is installed and passes DataNivra’s pack conformance kit through the real engine, but it cannot be activated yet: no plan includes it yet, the standard agent image does not ship it, the control-plane catalogue does not list it and the hosted sandbox has no synthetic estate for it. You can explore its synthetic records, masking and scenarios on this page and in the browser demo. Tell us if you need it: demand decides which packs become activatable next.
Which databases and files does the Logistics and supply chain pack work with?: Verified with this pack version: PostgreSQL and Local files (Parquet / CSV). 17 more connectors are compatible by capability: they support what the pack needs, but have not been verified with this pack yet.
How long does a first certified Logistics and supply chain dataset take?: Estimates, not guarantees — try the synthetic sandbox: minutes; install (or reuse) the agent: under an hour; connect a source: under an hour; review and approve policies: under an hour; first certified dataset: minutes.
Which test scenarios does the Logistics and supply chain pack include?: 11 runnable scenarios (everyday parcels, customs holds, failed deliveries, returns to sender and more), plus 1 negative-test scenario kept apart from valid data.
Do Logistics and supply chain rows leave my network?: No. The DataNivra agent runs inside your environment: it reads the source, masks, subsets, generates and certifies there, and sends only metadata, aggregate counts and evidence to the DataNivra control plane (customer-resident processing, zero raw-production-data egress).

Learn the concepts, then come back to activate

Regulatory context

The Logistics and supply chain pack covers data that laws and industry rules often treat as sensitive. It supports your privacy and governance programmes by keeping those records inside your environment and producing certification evidence; it does not, by itself, make any system or organisation compliant with any law, regulation or standard.

Try with synthetic data Notify me — tell us you need it

Everything on this page works without an account. Prefer a conversation? Request a demo (optional). Missing something? Request a feature.