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Eating the Elephant of Data Strategy

Paul Blogs on BI

As organizations look to design and create new data warehouses, lakes and even lake houses in the cloud and populate them with data from a combination of legacy on-premise data warehouses , new cloud applications and existing on-premise applications, they quickly realize this is a huge undertaking.

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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.

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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. Assessment and gap analysis Amazon faced scrutiny when its AI-powered recruiting tool was found to exhibit bias against women. Identify gaps related to ethics, transparency, risk and compliance.

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DPDP Act : Brace yourselves for the biggest game-changing legislation for India

CIO Business Intelligence

They should conduct a gap analysis comparing current practices against DPDP requirements to identify critical compliance deficiencies, to prevent reinvention of the wheel. Effective DPOs will balance compliance requirements with business objectives, facilitating responsible data innovation rather than simply implementing restrictions.

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