Key Takeaways: Lack of shared data definitions, ownership, and built-in compliance creates risk and inefficiencies across your organization. Business-friendly governance and stewardship frameworks...
Dialogue on an Inevitable Transformation Imagining the world in 2050 is a fascinating exercise. What will be the impact on businesses and the roles within them? Here, we focus on the role of the...
Key Takeaways: Data in organizations is typically managed by two distinct groups: data producers and data consumers. Data governance is essential in the age of data democratization, especially when...
Key Takeaways: Prioritize metadata maturity as the foundation for scalable, impactful data governance. Recognize that artificial intelligence is a data governance accelerator – and a process that...
Key Takeaways: Data integrity is essential for AI success and reliability – helping you prevent harmful biases and inaccuracies in AI models. Robust data governance for AI ensures data privacy,...
How compliant is your organization with the GDPR (General Data Protection Regulation) requirements that keep personal data only as long as needed for the purpose it was collected? How easily could...
Key Takeaways Data quality ensures your data is accurate, complete, reliable, and up to date – powering AI conclusions that reduce costs and increase revenue and compliance. Data observability...
Key Takeaways Data fabric and data mesh are modern data management architectures that allow organizations to more easily understand, create, and manage data for more timely, accurate, consistent, and...
Each of the following data mining techniques cater to a different business problem and provides a different insight. Knowing the type of business problem that you’re trying to solve will determine...
