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What characteristics must data have to prevent the collection of erroneous data or misinterpretation? This is the subject of this training.

Spoken language
Dutch
Language material
English
Half-days
1
Data

Introduction Data Quality (NL)

Tue 06 May 2025 09:00 - 16:30 Location: Utrecht
This training is conducted by: Gert-Jan Kooren
€800,- Enrol
Wed 05 November 2025 09:00 - 16:30 Location: Online
This training is conducted by: Gert-Jan Kooren
€800,- Enrol

What is Introduction Data Quality

The importance of data is ever increasing; many organizations cannot function without it, and far-reaching decisions are made based on it.

It can be disastrous if decisions are made based on incorrect or misinterpreted data.

Which characteristics define whether data is of sufficient quality to support processes and decision-making? In other words: when is the data “fit for use”? How can these characteristics be measured?

In this training, we will cover the various aspects of data quality, the methods that can be used to measure it, and the ways to present these measurements.

We will also discuss the main benefits and costs related to managing data quality.

During the training, the application of what you learn is central and you are challenged to work with the theory in practical cases.

The training is given by people with an extensive background in DQ Management. They know how it’s applied in practice and can therefore share “real-life” examples of data quality issues and the ways these were resolved.

Data quality is not just about theory. The expertise of our trainers adds a practical dimension to the theoretical concepts, providing real-world insights and best practices. This training will equip you with the knowledge and skills to recognize and improve data quality in your organization.


Who should attend Introduction Data Quality

  • Solution architects and designers of data-driven solutions (e.g., BI, advanced analytics, regulatory reporting)
  • Business Analysts and Information Analysts: Professionals who rely on data for business decision-making.
  • Data Stewards: Individuals responsible for data quality in an organization.
  • Data Analysts: Professionals who work with data daily and need to ensure its quality.
  • IT Managers: Individuals who oversee IT projects and need to understand the importance of data quality.
  • Project Managers: Professionals who manage projects involving large amounts of data.


Prerequisites

A basic understanding of data management concepts is beneficial but not mandatory.


Objectives

At the end of the training, you will be able to:

  • Understand the various forms of data quality and the business and IT perspectives on it.
  • Recognize the impact of low data quality on business processes.
  • Have a basic understanding of the methods available to measure and improve data quality.


e-CF competences with this course

  • B.1. Application Development
  • E.6. ICT Quality Management

Classroom, online, blended and in-company

At Capgemini Academy you learn in the way that suits you. Do you prefer classroom training, online or a combination of the two (blended)? You can follow most training courses in-company: within your own organization. We use a variety of tools to make learning even more fun and effective. Consider videos, games, quizzes, webinars and case studies, for example. And you can always contact your trainer with any questions.

Sfeerbeeld buiten met man in bordeaux overhemd

In-company training courses

With an in-company training you have several advantages:

  • You choose the location.
  • You train with your colleagues, ensuring it aligns with your practice.
  • The trainer tailors explanations, examples and assignments to your organization.
  • In consultation, exercises can be adapted to organization-specific questions.

Request more information or a quote.

Why Capgemini Academy?

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    Large training offer: both fully online and available in class.
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    Most training courses include certification and exam.
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    Trainers with passion, didactic skills and a good dose of practical experience as an IT professional.
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