Turn data challenges into opportunities with GenAI integration
We all know that data has become a crucial factor in decision-making and strategic planning of organizations. However, managing this asset has become complex as data volumes and complexity continue to increase.
It’s there that data governance and generative AI (GenAI) enter – two essential concepts that are transforming data management practices.
This article explores the synergy between data governance And GénAI and how they can improve data management practices.
Data governance refers to all processes, policies, standards and measures which ensure the effective and efficient use of information to enable an organization to achieve its objectives.
Three pillars are at the heart of data governance: data qualityensuring that data is accurate and fit for purpose; data security, protecting data against breaches and unauthorized access; And data privacyrespecting the user’s consent and legal constraints regarding the use of data.
The journey of data governance from its inception to its current state reflects the broader evolution of the digital landscape.
Initially, data governance primarily concerned data quality, regulatory compliance, and internal data management practices. This foundational phase was largely reactive, resolving immediate data issues and regulatory requirements.
1. Compliance and quality foundations
Initially, data governance frameworks were developed in response to regulatory pressures and the need for high-quality data in business operations.
