Are the Energy & Utilities 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 Energy & Utilities 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 Energy & Utilities pack include?

10 runnable scenarios (everyday supply, estimated reads, customers in arrears, meter exchanges and more), plus 1 negative-test scenario kept apart from valid data.

Do Energy & Utilities 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

Energy & Utilities industry pack

Synthetic customer, premise, metering, billing and field-service test data with linked masking

Preview only · not activatable yet Version 2.0.0 · 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 4 systems

7 cross-system relationships link billing, customer, field and metering; the pack's masking keeps one pseudonym per identity on every side. For example, customer.premises.premise_id and metering.meters.premise_ref get the same pseudonym.

The cases production samples rarely contain

8 ready-made scenarios generate them on demand, for example: reads estimated because no actual read was obtained, and bills issued on estimates; overdue bills, failed collections with reasons and payment arrangements for the debt; meters exchanged at the same premise, with the field visits that performed the exchange.

Sensitive fields found and masked before anyone sees them

37 columns across 10 entities are classified (direct identifier, financial, PHI, 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

10 entities across 4 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 12 relationships as a table

Relationships of the Energy & Utilities pack
Entity	References	Columns	Kind
Account	UtilityCustomer	`customer_id` → `customer_id`	Within a system
Account	Premise	`premise_id` → `premise_id`	Within a system
MeterRead	Meter	`meter_id` → `meter_id`	Within a system
MeterExchange	Meter	`old_meter_id` → `meter_id`	Within a system
BillPayment	UtilityBill	`bill_id` → `bill_id`	Within a system
Meter	Premise	`premise_ref` → `premise_id`	Across systems (pack relationship template)
MeterExchange	Premise	`premise_ref` → `premise_id`	Across systems (pack relationship template)
UtilityBill	Account	`account_ref` → `account_number`	Across systems (pack relationship template)
UtilityBill	Premise	`premise_ref` → `premise_id`	Across systems (pack relationship template)
PaymentArrangement	Account	`account_ref` → `account_number`	Across systems (pack relationship template)
ServiceOrder	Premise	`premise_ref` → `premise_id`	Across systems (pack relationship template)
ServiceOrder	Meter	`meter_ref` → `meter_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

Premise — `customer.premises` (synthetic)
`premise_id` sensitive	`street_address` sensitive	`city` sensitive	`postal_code` sensitive	`grid_ref` sensitive	`property_type`	`country_code`
PRM000000001	7093 Juniperwell Row	Orrinwick	99604	ZZ-GR-321252	HOUSE	ZZ
PRM000000002	2539 Willowmere Terrace	Orrinhaven	63528	ZZ-GR-937966	COMMERCIAL_UNIT	ZZ

Masking: before and after

Template Linked utility test data (UTL_LINKED_TEST_DATA) applied to a synthetic Premise record from customer.premises.

Synthetic record

Synthetic Premise record before and after masking
Column	Classified as	Before (synthetic)	After masking
`premise_id`	Direct identifier	`PRM000000001`	`PRM964250154`
`street_address`	PII, Quasi identifier	`7093 Juniperwell Row`	`7504 Willowmere Street`
`city`	Quasi identifier	`Orrinwick`	`Gantton`
`postal_code`	PII, Quasi identifier	`99604`	`65262`
`grid_ref`	Quasi identifier	`ZZ-GR-321252`	`SG-ZJ-950942`

Same pseudonym in two systems. The identifier PRM000000001 appears in customer.premises.premise_id and in metering.meters.premise_ref. Both become PRM964250154, so the masked systems still join (relationship UTL_METER_PREMISE).

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

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

Everyday supply

Normal UTL_EVERYDAY_SUPPLY

Ordinary customers, premises, accounts, meters, reads, bills and field visits

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

Preview in the browser demo: Everyday supply

Estimated reads

Rare UTL_ESTIMATED_READS

Reads estimated because no actual read was obtained, and bills issued on estimates

Valid but uncommon business situations that production samples often miss. Children per parent record: 2–4.

Preview in the browser demo: Estimated reads

Customers in arrears

Rare UTL_CUSTOMERS_IN_ARREARS

Overdue bills, failed collections with reasons and payment arrangements for the debt

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

Preview in the browser demo: Customers in arrears

Meter exchanges

Rare UTL_METER_EXCHANGES

Meters exchanged at the same premise, with the field visits that performed the exchange

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

Preview in the browser demo: Meter exchanges

Vulnerable customers

Rare UTL_VULNERABLE_CUSTOMERS

Customers registered for priority services with synthetic reasons

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

Preview in the browser demo: Vulnerable customers

Zero and negative consumption

Boundary UTL_ZERO_AND_NEGATIVE_CONSUMPTION

Reads at the consumption boundary: exactly zero (vacant premises) and negative corrections

Values at the edges of valid ranges (limits, thresholds, extremes). Children per parent record: 3–6.

Preview in the browser demo: Zero and negative consumption

Back billing

Rare UTL_BACK_BILLING

Back-bills catching up long unbilled periods after missing or faulty reads

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

Preview in the browser demo: Back billing

Outage surge

Rare UTL_OUTAGE_SURGE

A network outage: many outage-response visits within two days, one outage reference

Valid but uncommon business situations that production samples often miss. Children per parent record: 2–5.

Preview in the browser demo: Outage surge

Duplicate reads

Duplicate UTL_DUPLICATE_READS

Meter reads submitted twice with identical content under new read ids

Records that repeat others under new keys (clean-up and matching tests). Children per parent record: 2–4.

Preview in the browser demo: Duplicate reads

Supply histories

Historical UTL_SUPPLY_HISTORIES

Multi-year, referentially intact supply, read and billing histories without gaps

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

Preview in the browser demo: Supply histories

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

UTL_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.

UtilityCustomer — customer.utility_customers · 10 columns

A household or small-business customer.

Column	Type	Required	Sensitive classes
`customer_id` (key)	`VARCHAR(12)`	Yes	Direct identifier
`given_name`	`VARCHAR(64)`	Yes	PII, Direct identifier
`family_name`	`VARCHAR(64)`	Yes	PII, Direct identifier
`birth_date`	`DATE`	No	PII, Quasi identifier
`national_id`	`VARCHAR(16)`	No	PII, Direct identifier
`email`	`VARCHAR(128)`	No	PII, Direct identifier
`phone`	`VARCHAR(32)`	No	PII, Direct identifier
`priority_service_flag`	`BOOLEAN`	Yes	—
`vulnerability_reason`	`VARCHAR(32)`	No	PHI, Sensitive
`customer_since`	`DATE`	Yes	—

Premise — customer.premises · 7 columns

A supplied property / service point (the demo subset root: its accounts, holders, meters, reads, bills and field visits travel with it).

Column	Type	Required	Sensitive classes
`premise_id` (key)	`VARCHAR(12)`	Yes	Direct identifier
`street_address`	`VARCHAR(128)`	Yes	PII, Quasi identifier
`city`	`VARCHAR(64)`	Yes	Quasi identifier
`postal_code`	`VARCHAR(10)`	No	PII, Quasi identifier
`grid_ref`	`VARCHAR(16)`	No	Quasi identifier
`property_type`	`VARCHAR(16)`	Yes	—
`country_code`	`VARCHAR(2)`	Yes	—

Account — customer.accounts · 8 columns

A supply account (one fuel) of a customer at a premise.

Column	Type	Required	Sensitive classes
`account_number` (key)	`VARCHAR(12)`	Yes	Financial, Direct identifier
`customer_id`	`VARCHAR(12)`	Yes	Direct identifier
`premise_id`	`VARCHAR(12)`	Yes	Direct identifier
`fuel`	`VARCHAR(12)`	Yes	—
`tariff_code`	`VARCHAR(8)`	Yes	—
`status`	`VARCHAR(14)`	Yes	—
`payment_method`	`VARCHAR(16)`	Yes	—
`opened_on`	`DATE`	Yes	—

Meter — metering.meters · 7 columns

A meter installed (or formerly installed) at a premise.

Column	Type	Required	Sensitive classes
`meter_id` (key)	`BIGINT`	Yes	—
`meter_serial`	`VARCHAR(14)`	Yes	Direct identifier
`premise_ref`	`VARCHAR(12)`	Yes	Direct identifier
`fuel`	`VARCHAR(12)`	Yes	—
`meter_type`	`VARCHAR(12)`	Yes	—
`status`	`VARCHAR(10)`	Yes	—
`installed_on`	`DATE`	Yes	—

MeterRead — metering.meter_reads · 7 columns

A register read of a meter; consumption is the difference to the previous read.

Column	Type	Required	Sensitive classes
`read_id` (key)	`BIGINT`	Yes	—
`meter_id`	`BIGINT`	Yes	—
`read_at`	`TIMESTAMP`	Yes	Quasi identifier
`read_value`	`DECIMAL(12,3)`	Yes	Quasi identifier
`consumption`	`DECIMAL(12,3)`	Yes	Quasi identifier
`read_type`	`VARCHAR(10)`	Yes	—
`quality_flag`	`VARCHAR(12)`	Yes	—

MeterExchange — metering.meter_exchanges · 7 columns

Replacement of a meter at a premise by a new one (identified by its serial).

Column	Type	Required	Sensitive classes
`exchange_id` (key)	`BIGINT`	Yes	—
`old_meter_id`	`BIGINT`	Yes	—
`new_meter_serial`	`VARCHAR(14)`	Yes	Direct identifier
`premise_ref`	`VARCHAR(12)`	Yes	Direct identifier
`exchanged_on`	`DATE`	Yes	—
`reason`	`VARCHAR(20)`	Yes	—
`final_read_value`	`DECIMAL(12,3)`	Yes	Quasi identifier

UtilityBill — billing.utility_bills · 9 columns

A bill for one account and billing period.

Column	Type	Required	Sensitive classes
`bill_id` (key)	`BIGINT`	Yes	—
`account_ref`	`VARCHAR(12)`	Yes	Financial, Direct identifier
`premise_ref`	`VARCHAR(12)`	Yes	Direct identifier
`period_start`	`DATE`	Yes	—
`period_end`	`DATE`	Yes	—
`consumption`	`DECIMAL(12,3)`	Yes	Quasi identifier
`amount_due`	`DECIMAL(12,2)`	Yes	Financial
`bill_type`	`VARCHAR(10)`	Yes	—
`status`	`VARCHAR(16)`	Yes	—

BillPayment — billing.bill_payments · 9 columns

A payment or collection attempt against a bill.

Column	Type	Required	Sensitive classes
`payment_id` (key)	`BIGINT`	Yes	—
`bill_id`	`BIGINT`	Yes	—
`amount`	`DECIMAL(12,2)`	Yes	Financial
`paid_at`	`TIMESTAMP`	Yes	—
`method`	`VARCHAR(16)`	Yes	—
`payer_iban`	`VARCHAR(34)`	No	Financial, Direct identifier
`mandate_reference`	`VARCHAR(20)`	No	Financial, Direct identifier
`status`	`VARCHAR(10)`	Yes	—
`failure_reason`	`VARCHAR(24)`	No	—

PaymentArrangement — billing.payment_arrangements · 7 columns

An instalment plan agreed for an account in arrears.

Column	Type	Required	Sensitive classes
`arrangement_id` (key)	`BIGINT`	Yes	—
`account_ref`	`VARCHAR(12)`	Yes	Financial, Direct identifier
`arrears_balance`	`DECIMAL(12,2)`	Yes	Financial
`instalment_amount`	`DECIMAL(12,2)`	Yes	Financial
`days_in_arrears`	`INT`	Yes	—
`start_date`	`DATE`	Yes	—
`status`	`VARCHAR(10)`	Yes	—

ServiceOrder — field.service_orders · 10 columns

A field visit to a premise and one of its meters.

Column	Type	Required	Sensitive classes
`order_id` (key)	`BIGINT`	Yes	—
`premise_ref`	`VARCHAR(12)`	Yes	Direct identifier
`meter_ref`	`BIGINT`	Yes	—
`order_type`	`VARCHAR(16)`	Yes	—
`technician_name`	`VARCHAR(96)`	Yes	PII, Direct identifier
`scheduled_for`	`DATE`	Yes	—
`completed_at`	`TIMESTAMP`	No	—
`status`	`VARCHAR(10)`	Yes	—
`outage_ref`	`VARCHAR(12)`	No	—
`technician_notes`	`VARCHAR(400)`	No	Sensitive

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 Energy & Utilities
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 Energy & Utilities 2.0.0.
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 Energy & Utilities 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

`UTL_STRICT`

Every gate; full masking coverage; zero orphaned accounts, meters, reads, bills, payments, arrangements or field visits; exact row counts. Default for masked utility 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

`UTL_SCENARIO_TESTING`

Every gate, with slightly relaxed NULL-ratio drift for scenario datasets whose business states (open visits, successful collections, customers without priority services) 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 Energy & Utilities 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 Energy & Utilities pack or request a feature for it.

Downloads

Version 2.0.0, 61 files (199.9 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 7dbe07b478dd…
TROUBLESHOOTING.md 4.7 KB · SHA-256 0eb1283c1183…

Entity–relationship diagram (2)

er-diagram.mmd 4.2 KB · SHA-256 fad4fab23299…
er-diagram.svg 7.4 KB · SHA-256 a4ca28c6863e…

Sample schemas (5)

schema/billing.sql 1.9 KB · SHA-256 b8b543e15bc5…
schema/customer.sql 2.3 KB · SHA-256 efe1a536e8c9…
schema/entities.json 26.4 KB · SHA-256 99dc97bb15eb…
schema/field.sql 864 B · SHA-256 f3e2d02f950d…
schema/metering.sql 1.9 KB · SHA-256 82564837bd27…

Policy templates (9)

policies/README.md 1.3 KB · SHA-256 6d11d4bcebcc…
policies/UTL_ANALYTICS_UNLINKED.json 16.0 KB · SHA-256 f28e69a2cb36…
policies/UTL_CLASSIFICATION.json 203 B · SHA-256 74d22146ba2d…
policies/UTL_LINKED_TEST_DATA.json 18.0 KB · SHA-256 3c956d955657…
policies/UTL_REFRESH_WEEKLY.json 190 B · SHA-256 e54930bed540…
policies/UTL_SCENARIO_TESTING.json 549 B · SHA-256 a0728ad1a443…
policies/UTL_STRICT.json 549 B · SHA-256 df479db4f4bb…
policies/UTL_SUBSET_DEFAULT.json 112 B · SHA-256 d46c49c10d7c…
policies/UTL_VULNERABILITY_MINIMISED.json 18.0 KB · SHA-256 ab53c243ce03…

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

api/curl.sh 2.6 KB · SHA-256 35ae61f18dfd…
api/dataset-request.json 1.5 KB · SHA-256 79b68aa41288…
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 44 B · SHA-256 63808d040684…
ci/README.md 497 B · SHA-256 6d4ce7a12aa5…
ci/github-actions.yml 1.9 KB · SHA-256 496d2ed9e930…
cli.md 1.7 KB · SHA-256 51d71fca37ed…
sdk_example.py 1.6 KB · SHA-256 ec4c4af348ec…

Synthetic sample data (CSV, JSON, Parquet) (31)

synthetic/SYNTHETIC_MANIFEST.json 2.4 KB · SHA-256 6e6883297528…
synthetic/billing.bill_payments.csv 2.5 KB · SHA-256 76efd2d8392d…
synthetic/billing.bill_payments.json 7.9 KB · SHA-256 cb3607f5b2ea…
synthetic/billing.bill_payments.parquet 4.3 KB · SHA-256 3b7c037f6b8a…
synthetic/billing.payment_arrangements.csv 231 B · SHA-256 412dbed1da8d…
synthetic/billing.payment_arrangements.json 512 B · SHA-256 7d1c77407f13…
synthetic/billing.payment_arrangements.parquet 2.5 KB · SHA-256 2035877aa8b7…
synthetic/billing.utility_bills.csv 2.1 KB · SHA-256 041154848743…
synthetic/billing.utility_bills.json 6.9 KB · SHA-256 367512e8edc8…
synthetic/billing.utility_bills.parquet 3.6 KB · SHA-256 2c05e905ee71…
synthetic/customer.accounts.csv 871 B · SHA-256 cbf6e8bcb2e3…
synthetic/customer.accounts.json 2.3 KB · SHA-256 39219cb3560b…
synthetic/customer.accounts.parquet 2.7 KB · SHA-256 a7889f43c459…
synthetic/customer.premises.csv 519 B · SHA-256 bc3297e39c75…
synthetic/customer.premises.json 1.3 KB · SHA-256 05eade7ad7de…
synthetic/customer.premises.parquet 2.6 KB · SHA-256 4c16e6a928ad…
synthetic/customer.utility_customers.csv 746 B · SHA-256 addf1c2ef013…
synthetic/customer.utility_customers.json 1.9 KB · SHA-256 f5c8e476dd80…
synthetic/customer.utility_customers.parquet 3.5 KB · SHA-256 ebd60ffb05d4…
synthetic/field.service_orders.csv 1.1 KB · SHA-256 68129e4e003a…
synthetic/field.service_orders.json 3.0 KB · SHA-256 adbc81efbc3d…
synthetic/field.service_orders.parquet 3.9 KB · SHA-256 d871d99a6919…
synthetic/metering.meter_exchanges.csv 183 B · SHA-256 5262e7a5d135…
synthetic/metering.meter_exchanges.json 270 B · SHA-256 dbe5aa58d828…
synthetic/metering.meter_exchanges.parquet 2.5 KB · SHA-256 e947b10351e1…
synthetic/metering.meter_reads.csv 2.8 KB · SHA-256 2fe8a40d62c7…
synthetic/metering.meter_reads.json 9.7 KB · SHA-256 16c53c6bb7ea…
synthetic/metering.meter_reads.parquet 3.6 KB · SHA-256 3da87c22f097…
synthetic/metering.meters.csv 782 B · SHA-256 eda0dd478990…
synthetic/metering.meters.json 2.2 KB · SHA-256 74ba229e1a6a…
synthetic/metering.meters.parquet 2.6 KB · SHA-256 26737383384d…

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 Energy & Utilities 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 Energy & Utilities 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 Energy & Utilities 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 Energy & Utilities 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 Energy & Utilities pack include?: 10 runnable scenarios (everyday supply, estimated reads, customers in arrears, meter exchanges and more), plus 1 negative-test scenario kept apart from valid data.
Do Energy & Utilities 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 Energy & Utilities 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.

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