Data Governance

Govern your data to grow your business, stay compliant, reduce costs, and mitigate risks

Enabling efficiency through Data Governance

As the creation of data volumes and sources continue to grow, the big challenge that companies face is the continuous need to improve the value that they get from their data – without compromising its integrity. Data Governance ultimately helps you to find, understand and then use the data properly – helping with time to value.


Another huge driver of Data Governance is the increasing need to maintain the privacy and confidentiality of data, as well as meeting the requirements of a growing list of related compliance obligations – top concerns for government organisations and enterprise alike.


Having the right Processes, Policy and Roles in place gives you the authority to implement and facilitate a consistent and repeatable approach for the necessary data governance to comply – helping business' to derive value.

How it works

Implementing fixes to data quality without understanding the causes can be time consuming and expensive. Adopting data governance through a phased approach can help you understand the underlying causes and introduce efficient solutions that improve long term data accuracy.


When it comes to data governance, Experian can help your organisation adopt data governance, understand the impact of poor data and implement data quality solutions that improve overall data management efficiencies. Experian Pandora supports the development of a holistic data strategy and adoption of data quality as a management performance indicator, which can be the driving force in improving data management efficiencies.


Book a demo with our Experian sales representative today to understand how our data governance consulting services, software and data assets can set you on the path of data management efficiency.

How Experian can help

  • Achieve consistent and optimal best practice in data management across the organisation that can adapt with change

  • Maximise the value of data by identifying, quantifying and correcting data quality and process issues

  • Improve the return on investment in process and infrastructural investments around data quality through proactive monitoring

  • Enforce business and regulatory data policies ensuring any potential risks introduced through poor data processes are mitigated

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