What is Data Quality?

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Data Quality refers to the accuracy of datasets, and the ability to analyse and create actionable insights for other users. Key elements to reaching high-quality data are People, Processes and Technology.

Why is Data Quality important?

Data is arguably an organisation’s most important asset and therefore keeping it clean and up to date should be a key objective for any business. Five benefits of high-quality data include:

  1. It helps keep your data compliant with the latest Data Regulations (such as GDPR)

  2. Builds and maintains relationships with customers and prospects

  3. Decreases costs created by wastage

  4. Reduces errors and potential PR issues

  5. Enables you to become more agile with faster strategic decisions 

How do you achieve a successful data quality strategy?

People, technology and processes are key elements to any successful data quality strategy.

  • People - With 90% of organisations saying data is changing the way they do business, the Chief Data Officer role is becoming more and more integral to those looking to leverage their data. However, it's important to note the role all employees have as Data Stewards.
  • Technology - With data continuously growing in volume, variety and velocity but the demand for veracity and value higher than ever - data quality technology is having to keep up. Data Quality Management Tools (such as Experian Aperture Data Studio) have stopped being a 'nice to have' - and started to become a necessity.
  • Processes - Once you have the correct people and technology in place, you need to ensure that the proper systems are used so both are utilised properly. These processes need to be organisation-wide to cover all the necessary data.

How can I assess my data quality maturity?

Data Quality Maturity Assessment

Complete our short assessment and understand where your organisation sits on our maturity scale and what steps you can take to improve the quality of your data.