As AI and machine learning revolutionize industries, ensuring data security and integrity is paramount. But doing so in practice is not straightforward.
Organizations face a delicate balance: fulfilling AI’s promise of speed and innovation, with the imperative for cloud data governance and security. Leaning too far in either direction could have detrimental business impacts.
This DBTA Best Practices Report dives into the complexities – and opportunities – of data governance and security for the cloud and AI era. You’ll learn:
- Why only 23% of data managers fully trust the quality and accuracy of their data
- How the broad adoption of LLMs is changing the way we think about model training data
- 8 practical best practices for building an AI data governance framework
- How a data security platform helps de-risk AI and give you the freedom to get more value from your data and AI investments