Adaptive Data Governance

Discussion table

Learn from
Becky Pettifer
Becky Pettifer

Deputy Director, Migration & Borders Portfolio

Co-Host

Darren Brunt
Darren Brunt

Director Solutions Engineering

Co-Host

Darren Brunt is Pre-Sales Director UKI at Qlik. Darren’s key focus is delivering data-driven, innovation projects to enable digital leadership and transformation within high potential organisations using relevant, modern technologies. He helps relate how new technologies can help organisations transform and leverage data as a core asset for actionable insight and business benefit. Darren has more than 20 years experience in supporting organisations with their digital transformation journey
before joining Talend, Darren worked at HP and Software AG.
About the session

As technologies, regulations, and public expectations change, so too should the structures and processes governing data usage - such as data privacy, quality, integration, and accessibility. Government organisations that have a responsive and flexible approach to data management will be better able to leverage data for decision-making and service delivery while ensuring compliance with laws and regulations and addressing emerging risks and challenges.

  1. Regulatory Compliance: Adaptive Data Governance helps ensure ongoing compliance with evolving data privacy laws and regulations. How should you handle the technical translation of regulatory changes into data governance strategies - and how do you update these in a timely fashion?

  2. Quality Management: To ensure reliability of data, departments should also consider data lineage practices that enable tracking data from its origin through its lifecycle. How effective are the current data quality management tools and processes at your department in ensuring accurate, consistent, and reliable data, and where do you see room for improvement?

  3. Data Integration: Adaptive Data Governance can facilitate the integration of disparate data sources, enhancing inter-departmental collaboration and efficiency. How can we address the challenges of interoperability in terms of both technology and semantics when integrating data?