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Why clean data matters · Utilities

Equipment records that could not be tied to what was spent on them

A water utility trying to decide which pumps to replace finds that its asset register, its work orders, and its ledger each identify the same equipment differently.

Illustrative example. The organization and its data are invented to show a typical pattern. This is not a customer story.

What they hold

  • An asset register listing each pump, valve, and meter, with a location and an install date.
  • Work orders from field crews, recording what was done, where, and the parts used.
  • Operating expenses from the finance system, coded to cost centers.
  • Readings from monitoring equipment, exported by the vendor's software.

The mess

One pump, several identifiers

The register calls it PS-0412. Crews write PS412 or Pump Station 4 unit 12 on work orders. The finance system dropped the leading zero when the asset list was loaded from a spreadsheet, and knows it as PS-412. Nothing links the three.

Site names typed from memory

The same site appears as Riverside PS, Riverside Pump Stn, and River Side. Costs grouped by site are split across the spellings.

Readings in mixed units

Flow is recorded in liters per second by newer meters and gallons per minute by older ones, in the same column. The unit lived in the meter's configuration and was lost in the export.

Install dates that are placeholders

Equipment older than the register was given the first of January of the year the register was created. Those assets all look the same age, and younger than they are.

What it costs

  • Maintenance cost per asset cannot be calculated, so replacement is decided by opinion instead of by which equipment is actually costing the most.
  • Expenses that cannot be tied to an asset sit in a general account, and the true cost of running a site is understated.
  • A flow alarm threshold set for one unit is applied to readings in another, producing false alarms that crews learn to ignore.
  • Age-based replacement planning treats the oldest equipment as mid-life.
  • Regulatory reporting on asset condition takes a team weeks to assemble by hand.

What clean looks like

  • Each asset has one identifier, stored as text with its zeros intact, and a saved crosswalk records every alternative it has been known by.
  • Work orders and expenses carry that identifier, so cost per asset is a query instead of a project.
  • Site names resolve to one agreed list.
  • Every reading states its unit, and values are converted to one unit before comparison.
  • Unknown install dates are marked unknown, with an estimate held separately where one exists.

Problems in this example

Karg checks for many of these when it profiles a file, applies the fixes it is confident about, and sets the rest aside for your review. See how it works, or have our team clean your data for you.