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Technology adoptionPractitioner7 hrsIn person / Live online

Data You Can Actually Use

Why the report is wrong, and what to do about it. Covers the unglamorous work that decides whether anything downstream - dashboards, automation, AI - can be trusted.

Enquire about this course Explore what you’ll learn

Runs most often inFinancial services and bankingRetail and consumerLogistics and supply chain

What participants can do afterwards

  • Diagnose why two reports of the same thing disagree
  • Clean and structure a real dataset your team depends on
  • Set up a source of truth people will actually use
  • Recognise when a spreadsheet has outgrown itself
  • Stop the same data mess reforming in six months

Modules

4 modules, 7 facilitated hours.

  1. 1.Why the numbers disagree

    1.5 hrs

    Tracing two conflicting reports back to their sources.

    • Diagnose a disagreement between two reports

  2. 2.Cleaning and structuring

    3 hrs

    Hands-on with a real dataset the participants depend on.

    • Clean and structure a real working dataset

  3. 3.A source of truth

    1.5 hrs

    Agreeing where the number lives and who owns it.

    • Establish a source of truth people will use

  4. 4.Keeping it clean

    1 hrs

    Why clean data decays, and the ownership and checks that stop the same mess reforming.

    • Put checks in place that keep the dataset clean

How it is delivered

A facilitator runs the course live, in person or live online. Attendance is taken per session, participants submit work against the modules above, and a facilitator grades it. Those records stay with the organisation and can be exported.

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