Data Quality Management
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5 Disruptive Drivers for Data Quality Management
Data quality management has become increasingly important, as organisations are relying more heavily on data for their business operations than ever. And this will intensify. There are five main drivers for data quality management:
Data Complexity: Organisations are now dealing with data from multiple sources in multiple formats. This makes it extra challenging to ensure accuracy and consistency.
Regulatory Compliance: Organisations must be compliant with various regulations, such as GDPR, HIPAA, and CCPA. The quality of the data is crucial in order to assure compliancy.
Business Intelligence: Today’s organisations are increasingly relying on data-driven decision-making. The quality of the data itself and the trust in data determines effective decision making.
Data Volume: Organisations are now dealing with vast amounts of data, which can be difficult to manage and deal with. Managing the quality of the data needs extra thought.
Globalisation: More and more organisations are operating in a globalised environment, which means they must manage data from multiple sources in multiple languages, timezones and formats. Ensuring accuracy and consistency is complex in this heterogenous, global environment.
These five disruptive drivers are driving the need for data quality management and are determining the way organisations manage their data.
How to improve data quality
To ensure data quality you can follow a number of best practices:
Establish data quality standards and ensure they are met.
Profile and measure data quality to assess accuracy and consistency.
Monitor and assess data quality on an ongoing basis.
Educate employees and third parties on your data quality standards and best practices and give feedback about current status on a regular basis.
Use effective data quality tools to help you monitor and assess data quality.
Establish data governance to manage your data assets in a structured and transparant fashion.
These best practices can help you to optimise data quality and maximise the value of your data.
