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Description

Data Quality: Measuring, Correcting and Making Analysis Reliable

Measure the quality of a dataset and correct what genuinely distorts your analysis

  • 0.43 days — 3 h
  • In-person or virtual
  • Intermediate
  • Up to 6 participants

A dashboard loses its credibility the moment a single figure is challenged. Duplicate customer records, inconsistent coding, empty fields and illogical dates spread silently all the way through to the indicators. Corrections are made case by case in the reports rather than at source, and the same discrepancy reappears in the following cycle.

A short instant-learning session focused entirely on data quality. You define measurable quality dimensions. You build controls and profile the dataset. You then distinguish one-off correction from escalation to source and prepare an action plan with the business teams.

Learning objectives

  • Define measurable quality dimensions for a dataset
  • Carry out profiling to identify the dominant anomalies
  • Build control rules and a quality indicator
  • Handle duplicates, missing values and inconsistent coding
  • Organise the escalation of corrections to the source application

What makes this programme different

Profiling is carried out live in the session on an extract brought by participants
The control rules written during the session remain reusable afterwards
Each anomaly is arbitrated between cosmetic correction and correction at source

Programme

1Quality Dimensions and Measurement

Turning the problem into figures

  • Defining accuracy, completeness, consistency and timeliness
  • Choosing the dimensions relevant to how the data is used
  • Building a quality indicator for each dimension
  • Agreeing an acceptance threshold with the business

2Profiling and Anomaly Detection

Looking at the data before correcting it

  • Analysing distribution and extreme values
  • Spotting duplicate records and duplicated keys
  • Detecting inconsistent formats and coding schemes
  • Identifying empty fields and default values

3Correction and Long-Term Reliability

Treating the cause rather than the symptom

  • Choosing between automated correction and business arbitration
  • Writing standardisation and deduplication rules
  • Escalating anomalies to the source application
  • Tracking quality trends over time

Who is it for

Data analysts · management controllers · master data owners and business intelligence project managers dealing with contested indicators.

Prerequisites

Ability to work with a structured dataset and read a simple query.

Dates & locations

12 scheduled dates between November 2026 and December 2027. Seats are confirmed in the order enquiries are received.

November 2026

December 2026

January 2027

February 2027

March 2027

April 2027

May 2027

June 2027

September 2027

October 2027

November 2027

December 2027

None of these dates suit you? We open additional sessions on request, and any programme can be run privately for your team.

Practical details

Before the programme
Online positioning questionnaire. Your development objectives are shared with the trainer, who tailors the practical case studies to your context.
Teaching methods
Theoretical input, workshops and practical case studies. Digital course materials and method sheets provided.
Assessment
Multiple-choice tests and role-play exercises. Assessment of learning at the start and end of the programme, with immediate and 60-day follow-up evaluations.
After the programme
One year of access to the e-learning platform. Self-assessment of the skills acquired and a 30-day follow-up session with your trainer.
How to register
Registration online or on the basis of a quotation.
Lead time
11 working days after confirmation of registration.
Accessibility
Accessible to people of determination. Contact our accessibility coordinator to design a suitable solution: contact@mpf-academy.ae
Start dates
Rolling intake: in addition to the scheduled sessions, this programme can start on request.