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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

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AI adoption accelerates as enterprise PoCs show productivity gains

CIO Business Intelligence

“Data is the lynchpin to AI success,” says Nafde. Start with your data strategy before your AI strategy, and align your AI strategy with your business strategy.” This can help companies accelerate the use of AI while they continue to curate their internal data and harvest their expertise.”

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

In this article, we’ll dig into what data modeling is, provide some best practices for setting up your data model, and walk through a handy way of thinking about data modeling that you can use when building your own. Building the right data model is an important part of your data strategy. Discover why.

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The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

“We are also working to factor in the COVID impact when making sense of the data and, more importantly, when communicating it.”. Chris and his team are increasing the volume of data being captured and using automation to augment their data strategy : “This is a real jump forward for us.