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Quality assurance of data and analysis

Quality assurance of data and analysis involves sorting and cleansing information so that any conclusions based on it can be made with confidence.

Geciteerd uit het UK GDaD PCF.

Niveaus

1. Bewustzijn

You can:

  • describe some basic data issues and how to check that data and analysis look right
  • explain the concept of data being fit for purpose, and the context of the data
  • describe some methods for preparing data for analysis
  • describe quality assurance processes
2. Toepassend

You can:

  • identify appropriate ways to collect, collate and prepare data
  • decide if data and analysis is accurate and fit for purpose
  • perform data preparation and cleansing with limited guidance
  • undertake quality assurance processes
  • peer-review colleagues’ outputs from data analysis to ensure quality
3. Ervaren

You can:

  • set up a system to get data ready for use
  • specify how data should be cleansed and prepared
  • bring data together from different sources
  • communicate the limitations of data
4. Expert

You can:

  • set up tools and systems for effectively assuring data and analysis across multiple teams
  • use appropriate approaches for verifying and validating data and analysis
  • influence senior stakeholders over data and analysis approaches
  • coach and mentor others in assuring data and analysis

Contains public sector information from the UK Government Digital and Data Profession Capability Framework (https://understand-digital-data-roles-skills.service.gov.uk/), licensed under the Open Government Licence v3.0. © Crown copyright.

Dichtstbijzijnde vaardigheden in ESCO

Contains ESCO v1.2.1 data (https://esco.ec.europa.eu/). © European Union. Reuse authorised under Commission Decision 2011/833/EU.

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