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Data quality

Location data ages quickly, and sources change without notice. That is why verification is a fixed part of every delivery.

  • Count reconciliation
  • Place check
  • Coordinates
  • Address structure
  • Duplicates
From our processing

One location, before and after

This is how a record arrives from a store finder – and how it leaves. Seven interventions every location goes through.

  1. address Musterstr.12
    str + number Musterstr. | 12 Street and house number in separate fields
  2. place 12345 Musterstadt
    zip + city 12345 | Musterstadt Postcode and place separated
  3. phone +49 (0)123 456 - 789
    phone 0123/456789 Area code separated by a slash, consistent across all networks
  4. homepage WWW.Beispiel.DE/Markt
    web www.beispiel.de/markt Lower case throughout, including the path
  5. coordinates 10.000000 / 50.000000
    lat + long 50.000000 | 10.000000 Latitude and longitude were swapped
  6. opening Mon to Sat 7.30am – 9pm
    openings Mo-Sa 07:30-21:00 Fixed notation, machine-readable
  7. fax —
    fax stays empty What the source does not provide is not estimated

The location shown is invented. The interventions are not – they run across the entire dataset with every delivery.

Across the whole dataset

Six checks before every delivery

What is invisible in a single record only shows in the whole – a missing branch, a duplicated location, a coordinate outside the delivery area.

  1. 01

    Count reconciliation

    against the previous delivery

    If the number of locations differs from the previous delivery, the cause is investigated – a rebuilt store finder looks just like a market decline.

  2. 02

    Place and postcode

    against 10,939 municipalities

    Checked against the official register of municipalities – the municipality is delivered, not the district.

  3. 03

    Coordinate position

    within the delivery area

    Swapped or empty coordinates are caught before they end up on a map.

  4. 04

    Address structure

    field by field

    Street and house number separated, suffixes and range details kept.

  5. 05

    Phone numbers

    format and length

    Consistent format, extensions kept, head-office numbers do not count as a location number.

  6. 06

    Duplicates

    across the whole dataset

    Matched via normalised street and place keys, not via text comparison.

Traceable, not smoothed over

Every delivery comes with a change count: new, gone, changed.

If a network shrinks, we deliver the smaller number and say why.

  • The same field structure in every delivery, across all store networks
  • Stable identifiers, so your dataset can be kept up to date
  • Empty fields instead of estimated values
  • An explanation for conspicuous changes in counts
  • Notice if a store network can no longer be collected

An empty cell is honest. A guessed cell does damage no one notices.

Have a dataset checked?

We look at an existing dataset and tell you where the gaps, duplicates and format errors are.

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