-
Building an effective AI Governance framework using your Data Catalog
Empower responsible AI with a data-driven governance framework built on your data catalogue. Ensure ethical, transparent AI by aligning data, models, and stakeholders.
-
The Importance of Proactive Data Governance: Avoiding Acts of Omission
Data management asleep at the wheel? Proactive data governance is your wake-up call. Avoid acts of omission and unlock the power of your information. #datagovernance #cybersecurity #innovation #KingIV
-
Key KPIs: Measuring the Success of Your Data Governance Program
5 KPI categories (business, operations, data, technology and literacy) provide a multi-faceted approach to measuring and optimising your data governance program.
-
MDM and the Single View of the Customer: Partners, Not Twins
A single view of the customer extends master data management by provided contextual data for better insights. Without accurate master data the single view may fail to deliver due to inherent data quality issues.
-
Data Quality and Master Data Management
Boost your data game with powerful tips! Learn how data quality and MDM can be your secret weapon for accurate decisions, enhanced compliance, and streamlined processes. Dive into proven best practices and start winning with good data!
-
Explaining explainable artificial intelligence (XAI)
Explainable AI (XAI) is a field of artificial intelligence that ensures that process followed by machine learning models can be explained and understood by humans. It is critical for high stakes AI
-
The Importance of Protecting Your Customer’s Data in 2024
Every company must prioritise the protection of customer data from cyber crimes
-
Building the Foundation for AI Success: The CDO’s Role
Understand the critical role of the CDO in delivering successful AI initiatives
-
Linking AI Products to Business Value – shifting from hype to outcome
To unlock the true potential of AI, organizations must link AI products to tangible business outcomes. This post explores how Information value management (IVM) principles can be applied to AI to ensure tangible benefits.
-
Which Comes First, Data Governance or Data Quality?
Determining whether data governance or data quality comes first is a bit like the chicken and egg conundrum. Both are integral and interdependent. However, it’s helpful to think of it as a cyclical relationship rather than a linear sequence. Tactical data quality initiatives can deliver quick results to meet specific project data goals, but for…
Data Quality Matters 