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DataOps Workbench

Use DataOps Workbench to turn sources, tags, files, and records into reusable asset context, canonical graph relationships, API products, and MCP-ready data.

Data engineers, OT engineers, solution architects, and product owners preparing trusted operational context.

Before you start

What to have ready

At least one registered source or planned source connection.

A target asset class, system, or operating workflow.

Naming standards for assets, tags, units, and sites.

A decision about which modules or APIs will consume the output.

Usage workflow

How to use DataOps

01

Register sources

Add operational sources and capture ownership, source health, connection pattern, and expected refresh behavior.

02

Inspect tags and records

Browse tags, topics, tables, and files to understand signal quality, units, naming, and missing context.

03

Map models and instances

Create asset models, bind instances, normalize fields, and connect source data to equipment, systems, and locations.

04

Build graph and namespace context

Use canonical graph, namespace, and standard profiles so modules and AI agents share the same operational meaning.

05

Publish and monitor products

Publish governed API/MCP products, run pipelines, and monitor freshness, validation, and data product health.

Need help?

Get implementation guidance

Request DataOps readiness help when mapping, standards, or source quality blocks the first workflow.

Talk to TwinEdge