Curated guidance for integrating SCADA/OT data with BI and decision workflows in manufacturing and industrial operations.
A practical, stepwise recipe for ingesting SCADA/OT data, aligning timestamps and labels, making time-series data queryable for BI teams, and producing reliable operational KPIs while preserving OT security and reliability.
A practical operational playbook for modeling, aggregating, and monitoring time-series data from sensors, SCADA/OT, IoT, logs and product metrics. Provides concrete patterns for aggregation windows, irregular sampling, seasonality and holiday adjustments, baseline forecasting for anomaly detection, alerting strategy and escalation, dashboard design, and evaluation metrics — with common pitfalls and sample queries to apply immediately.
A practical, operational playbook for scoping predictive‑maintenance use cases, choosing sensors, creating target labels, validating models, integrating alerts into maintenance workflows, and keeping models and people aligned over the asset lifecycle.
A practical, operations‑focused playbook for framing predictive‑maintenance use cases, choosing sensors and features, labeling and validation strategies (including lead‑time analysis), integrating models into maintenance workflows, tuning alarms, and defining clear human‑in‑the‑loop responsibilities so predictive signals become trusted, actionable work.