Remove Data Governance Remove Gap analysis Remove Risk Management
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Beyond the hype: Key components of an effective AI policy

CIO Business Intelligence

Data governance Strong data governance is the foundation of any successful AI strategy. It’s essential to regularly audit your AI systems to detect and mitigate biases in data collection, algorithm design and decision-making processes. Identify gaps related to ethics, transparency, risk and compliance.

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The art and science of data product portfolio management

AWS Big Data

In the same way, overly restrictive data governance practices that either prevent data products from taking root at all, or pare them back too aggressively (deforestation), can over time create “data deserts” that drive both the producers and consumers of data within an organization to look elsewhere for their data needs.