# Industrial data and analytics

[Website page](https://www.gt-intelligence.com/services/industrial-data-analytics)

GTMI builds data models, pipelines, reporting stores and dashboards for manufacturing. We use approved source access and agree each measure with its operational owner.

For operations, engineering, and data teams planning production reporting or an industrial analytics pipeline.

## Data engineering and reporting in one scope

GTMI can build the data pipeline and reporting application, or deliver a specific part of that work. Work includes source inventories, tag and event models, transport, storage, calculations, access rules, and dashboard implementation. We first identify who or what will use the data and what the report must show. That determines the sources and interfaces needed within your manufacturing environment.

## Model the data and define its ownership

Source work can span PLC, SCADA, MES, historian, ERP, quality, and manual inputs. GTMI documents event meaning, timestamps, identifiers, calculation rules, and handling of missing or corrected records. We review metric definitions with the client’s operational owners and document the data-quality checks and responsibilities alongside the model. The resulting definition gives production reviewers a consistent basis for selecting the figures to use, comparing shifts and investigating a disputed result.

## Implement a supported reporting path

Delivery can use MQTT or API transport, historian and time-series patterns, PostgreSQL stores, and Grafana or Power BI, depending on the environment. For execution systems, the design uses approved read-only interfaces or API boundaries and separate analytics storage where required. GTMI implements the agreed pipeline and reporting views, checks them against source records, and documents refresh, access, and support responsibilities.

## You own the measure and its use

The client approves metric definitions and decides how reported information is used in production. Source system owners approve data access and any changes at the source. GTMI is responsible for the agreed data model, pipeline, and reporting implementation. Where reporting touches a regulated system, its boundary and any validation implications are reviewed through the client’s quality process before the access pattern is accepted.

## Scope the reporting or data work

Tell us which decision the report supports and why the figures are disputed or difficult to use. We can identify whether the work belongs in source capture, the measure definition, the pipeline or the reporting view. Existing reports and source samples can follow later.

## Data and reporting deliverables

- Source inventory and approved metric definitions
- Tag, event, and reporting data models
- Implemented pipelines and consumer access
- Reporting views and operating documentation

## Data design and reporting delivery

Start with an architecture package for a reporting requirement, or scope the implementation of its pipeline and views.

### Data architecture package

Source, model, transport, and access design for a named reporting requirement, ready for client review.

### Pipeline and reporting delivery

Implementation of the agreed data path and reporting views, including checks against the sources and handover.

Reporting access follows source-system approvals. Operational owners approve the metric and the decisions made from it.

## Starting material

A reporting brief, sample source records, intended users, and access requirements.

## Platforms

PostgreSQL, TimescaleDB, InfluxDB, MQTT, Grafana, Power BI