DFS Lite
DFS Lite is the connection and ingest layer of Data Fusion Services. Use it to connect source systems, inspect source data, map values to operational targets, and monitor whether data is fresh and usable.
DFS Lite operating flow
Prerequisites
- Tenant access and DFS read/write permission.
- Source endpoint, credentials, file, topic, table, node, or network details.
- Target asset, point, dataset field, work record, or scene context.
- A source owner who can confirm meaning, units, timestamp, and expected range.
What users do in DFS Lite
| Task | UI area | Result |
|---|---|---|
| Create a source connection | Connectors | A connector is saved and can be tested. |
| Start, pause, or sync a source | Connector List or Connector Detail | Data collection is controlled by an operator. |
| Browse source structure | Connector Wizard or Detail | Equipment, tags, files, topics, tables, or fields are visible. |
| Preview values | Connector Wizard or Detail | Sample timestamps and values can be checked before mapping. |
| Map fields | Mapping step or Mapping tab | Source values are bound to target entities and fields. |
| Review mapping suggestions | Mapping suggestions | AI-assisted suggestions are reviewed before use. |
| Check quality | Data Quality | Completeness, timeliness, accuracy, trends, and quota are visible. |
| Diagnose sync runs | Sync History | Read, written, and failed counts are visible. |
Governed source intake
DFS Lite should capture enough context for the source to be reused safely later. A working connector is only the first checkpoint. Before a source is promoted to DFS Pro, confirm that the data owner, credential boundary, schema, preview sample, and sync quality are all understood.
| Intake area | What to check | Why it matters |
|---|---|---|
| Source contract | Owner, endpoint, source purpose, refresh cadence, required fields, and readiness status. | Gives downstream teams a clear basis for reuse and approval. |
| Credential binding | The connector uses the deployment's credential store, and secrets are not copied into mapping notes or handoff documents. | Keeps operational access separate from documentation and configuration review. |
| Browse and preview | Equipment, tables, topics, files, fields, sample values, and timestamps match the source owner's expectation. | Finds schema drift and wrong-source issues before data is reused. |
| Mapping review | Target identity, units, timestamp semantics, and transform expressions are checked with the source owner. | Prevents live values from being interpreted as the wrong asset, point, or metric. |
| Sync evidence | Test connection, latest sync result, failed counts, and quality status are visible. | Lets teams distinguish source outages from downstream data issues. |
| Promotion readiness | The source has a steward, known schema, expected cadence, and an agreed downstream consumer. | Defines when the source is ready to become a governed DFS Pro dataset. |
For implementation projects, keep this intake record close to the connector. It becomes the evidence used when a dataset, fusion task, MDM resolver, or AI Agent workflow depends on the source.
Connector types
DFS Lite supports several source families. Availability can depend on deployment and customer environment.
| Type | Typical source |
|---|---|
| OPC UA | Industrial automation systems and equipment telemetry. |
| BACnet | Building automation systems and facility points. |
| Modbus | Devices and controllers with register maps. |
| MQTT | IoT brokers, topic streams, and JSON payloads. |
| REST | Enterprise APIs, cloud services, and custom services. |
| CSV | Uploaded files, exports, and watched file drops. |
| JDBC | Databases, historians, and reporting tables. |
| Fabric | Microsoft Fabric or lakehouse-oriented integrations when enabled. |
Lite to Pro handoff
DFS Lite data can remain as live connector data when the use case only needs current operational status. Move data into DFS Pro when the team needs governed datasets, repeatable fusion, review queues, lineage, or BI reporting.
| Use DFS Lite when | Move to DFS Pro when |
|---|---|
| You are validating a source connection. | The data must become a reusable dataset. |
| The workflow needs live mapped values. | The data needs a steward, lifecycle, profile, or version history. |
| The team is checking source freshness. | Multiple datasets need to be fused. |
| The use case is connector troubleshooting. | Conflicts or rejected rows require formal review. |
Validation checklist
- The connector test result is recorded.
- Source preview shows expected values and timestamps.
- Mapping identity, target field, units, and transform expression are reviewed.
- Sync history shows an explainable read, written, and failed count.
- Data quality status is visible to the downstream workflow owner.
- Known limitations are recorded before handoff or promotion to DFS Pro.
Read next
| Page | Use |
|---|---|
| Connectors | Create, test, start, pause, sync, and monitor connectors. |
| Mappings | Map source fields to operational targets. |
| Data Quality | Check completeness, timeliness, accuracy, quota, and sync health. |