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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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‘Phase Two’ of Europe’s Data Transformation

Corinium

For the UK and Europe’s most data-led companies, phase one of the data transformation is now complete. The strategies have been agreed, the foundations have been laid and the real work is well underway.

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4 Considerations When Building Your Government Data Strategy

Cloudera

If you’ve followed Cloudera for a while, you know we’ve long been singing the praises—or harping on the importance, depending on perspective—of a solid, standalone enterprise data strategy. The ways data strategies are implemented, the resulting outcomes and the lessons learned along the way provide important guardrails.

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‘Phase Two’ of Europe’s Data Transformation

Corinium

For the UK and Europe’s most data-led companies, phase one of the data transformation is now complete. The strategies have been agreed, the foundations have been laid and the real work is well underway.

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What companies get wrong about data transformation

CIO Business Intelligence

So if funding and C-suite attention aren’t enough, what then is the key to ensuring an organization’s data transformation is successful? Companies that commit to treating data as a product and to transforming their culture are the ones that succeed, says Doug Laney, innovation fellow of data and analytics strategy at West Monroe.

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Data strategy is a differentiator for universities. Here’s how to get it right

CIO Business Intelligence

Data is critical to success for universities. Data provides insights that support the overall strategy of the university. Data also lies at the heart of creating a secure, Trusted Research Environment to accelerate and improve research. The first step is to put in place a robust data strategy.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

In this article, I am drawing from firsthand experience working with CIOs, CDOs, CTOs and transformation leaders across industries. I aim to outline pragmatic strategies to elevate data quality into an enterprise-wide capability. This challenge remains deceptively overlooked despite its profound impact on strategy and execution.