Checklist

SCADA & OT Integration Checklist for BI

An interactive, practical checklist to guide teams through integrating SCADA/OT telemetry with enterprise BI. Covers inventory, time alignment, sampling, tagging, asset mapping, contracts, latency, security, provenance, quality checks, example KPI queries, monitoring, and implementation ownership.

Interactive Tool

SCADA & OT Integration Checklist for BI

This checklist helps operators, engineers, data teams, and BI owners work together to turn SCADA and OT telemetry into reliable, actionable business intelligence. Use it to reduce risk, align KPIs to real-world constraints, and prepare data for analysis while preserving security and provenance.

Confirm that every sensor/source is inventoried with ID, type, physical location, tags, and owning team/role.
List missing sensors, naming conventions, duplicate IDs, or special cases to resolve.
Confirm timestamps are normalized (timezone, format) and documented for every source.
Example: ISO-8601 UTC; indicate if device-local clocks are used and how offsets are handled.
Confirm agreed sampling rates, down-sampling/aggregation windows, and when raw high-resolution data is retained.
Describe default sample rates, aggregation (e.g., 1s -> 1m median), and exceptions for events.
Confirm how anomalies are detected, tagged, and stored so BI queries can filter or flag events.
Select the primary method used to identify anomalies or events.
Confirm assets are mapped consistently (site > line > cell > machine > component) with master asset IDs.
Include parent-child relationships, mapping rules, and links to master asset registry.
Confirm agreed fields, types, update frequency, and SLAs between OT producers and BI consumers.
Person, role, or team accountable for the contract.
Define acceptable latency for each consumer (real-time alerts vs. hourly KPIs).
Enter numeric seconds. Use larger units if appropriate and document for each use case.
Confirm network segmentation, credential management, encryption, and disaster/redundancy plans.
List outstanding issues, remediation actions, and compliance requirements.
Confirm that source identifiers, timestamps, transformations, and versioning are recorded and queryable.
Describe where lineage is stored (metadata store, data catalog) and how to access it.
Confirm routines for checking gaps, spikes, duplicates, and sensor drift are scheduled and documented.
Choose the primary approach for handling missing or invalid data in KPI calculations.
Confirm that validated example queries and unambiguous KPI definitions exist for common measures.
Include SQL, time-series query, or pseudocode for OEE, MTTR, availability, throughput, etc., and point out assumptions.
Confirm target BI tools, formats (Parquet, CSV, API), and transfer mechanism (push, pull, stream).
List tools such as Power BI, Tableau, Grafana, enterprise data lake, MQTT broker, etc.
Confirm alerts for pipeline failures, metric drift, data latency violations, and data-quality regressions.
Describe thresholds, responsible on-call or team, and escalation paths.
Confirm tasks, owners, timeline, and acceptance criteria are documented and agreed.
Team or role responsible for execution.
YYYY-MM-DD or freeform date for delivery.
Name, date, acceptance criteria met, and any follow-up items.
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