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Keep every reading
Interval data retained in full rather than aggregated away at the point where the detail still mattered.
Utilities operate on two clocks at once: assets measured in decades and demand that changes by the second. Software built for one is usually wrong for the other.
Used for metering, grid telemetry, customer systems and regulatory reporting.
What this looks like in practice
Interval data retained in full rather than aggregated away at the point where the detail still mattered.
An outage brings every customer to your systems at once. That is exactly when they must work.
Infrastructure lasts decades. The data about it should be readable for as long.
Spend that can be explained to a regulator as a plan rather than as a consequence.
Utilities have historically summarised data at ingestion because storing it all was uneconomic. Every one of those summaries is a question that can no longer be asked.
Supply fails and every affected customer reaches for the same page within minutes. Historically that is a second failure layered on the first, and the one customers remember. Capacity that follows arrival turns the worst operational hour into an ordinary one for everybody not holding a torch.
Every reading kept, so later questions are answerable from data rather than inference.
Field applications improving at a normal cadence instead of a generational one.
What is out, what is coming back, and when — for customers and for operations.
Market and regulatory reporting assembled from the record rather than reconstructed.
We stopped summarising at ingest. Six months later our forecasting team told us they finally had the inputs they had been asking for since I joined.
Yes, and most teams here find the economics have changed more than they realised. The aggregation decisions in your pipeline were usually made under constraints that no longer apply.
They scale with arrival, which is the point: the hour when every customer contacts you is the hour those systems are judged on.
As a cost you planned and can explain, with a record of what was spent and why. That is a materially easier conversation than a variable you reconcile afterwards.
It is assumed. Data remains readable on the asset’s horizon rather than the software’s, and what you build stays portable so a platform decision is not a thirty-year commitment.
Run regulated workloads with a complete record of every change, and answer an auditor in an afternoon rather than a quarter.
Carry sensitive workloads with separation that is structural, and keep clinical and research software moving.
Serve the public on infrastructure that stands up to scrutiny, procurement and a service that cannot be allowed to fail.
Hold up on the day that matters most, and change your storefront in the week you decided to, not the quarter after.
Publish the moment it matters, carry an audience that arrives all at once, and keep an archive that stays reachable.
Bring plant data somewhere useful, keep the software near the line dependable, and stop treating the factory as offline.
Begin with one workload. Keep what you have running. Decide whether to continue once you have seen it carry something real.
No migration required to begin. Nothing to tear down if you stop.