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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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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

How to make smarter data-driven decisions at scale : [link]. The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. A lot has changed in those five years, and so has the data landscape. But if they wait another three years, they will never catch up.”

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CIOs can and should play a pivotal role in ESG strategy

CIO Business Intelligence

This article was co-authored by Katherine Kennedy , an Associate at Metis Strategy. The ability to provide transparent, data-driven insights and measure progress toward ESG commitments makes the technology leader critical to the success of any ESG strategy. Smarter operations through integrated data and analytics.

Strategy 110
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Best Ways to Integrate Big Data into Your Business

Smart Data Collective

This information, dubbed Big Data, has grown too large and complex for typical data processing methods. Companies want to use Big Data to improve customer service, increase profit, cut expenses, and upgrade existing processes. The influence of Big Data on business is enormous. Where does big data come from?

Big Data 104
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AI this Earth Day: Top opportunities to advance sustainability initiatives

IBM Big Data Hub

To drive real change, it’s crucial for individuals, industries, organizations and governments to work together, using data and technology to uncover new opportunities that will help advance sustainability initiatives across the globe. The world is behind on addressing climate change.

IoT 83
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Using Artificial Intelligence to Make Sense of IoT Data

BizAcuity

IoT is basically an exchange of data or information in a connected or interconnected environment. As IoT devices generate large volumes of data, AI is functionally necessary to make sense of this data. As IoT devices generate large volumes of data, AI is functionally necessary to make sense of this data.

IoT 56
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AI-First Benefits: 5 Real-World Outcomes

Cloudera

The availability and maturity of automated data collection and analysis systems is making it possible for businesses to implement AI across their entire operations to boost efficiency and agility. Among the benefits of AI-first strategies are: Operational efficiency. Such human frailties are not an issue for AI-driven systems.