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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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The data flywheel: A better way to think about your data strategy

CIO Business Intelligence

This article was co-authored by Duke Dyksterhouse , an Associate at Metis Strategy. Data & Analytics is delivering on its promise. Some are our clients—and more of them are asking our help with their data strategy. Often their ask is a thinly veiled admission of overwhelm. We discourage that thinking.

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Unlocking the Power of AI with a Real-Time Data Strategy

CIO Business Intelligence

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. Titanium Intelligent Solutions, a global SaaS IoT organization, even saved one customer over 15% in energy costs across 50 distribution centers , thanks in large part to AI. Instant reactions to fraudulent activities at banks.

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5 recommendations to get your data strategy right

IBM Big Data Hub

The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. The evolution of a multi-everything landscape, and what that means for data strategy.

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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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Cloudera: Enabling the Cloud-Native, Data-Driven Techco

Cloudera

In addition to that, the march of network virtualisation combined with the cloudification of IT have driven further changes in operations. Their processes are ‘data driven’, their networks are trending towards automation, and AI systems are powering customer engagement in store , online and at home.

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Prioritizing Data: Why a Solid Data Management Strategy Will Be Critical in 2024

Ontotext

In 2023, data leaders and enthusiasts were enamored of — and often distracted by — initiatives such as generative AI and cloud migration. I expect to see the following data and knowledge management trends emerge in 2024. However, organizations need to be aware that these may be nothing more than bolted-on Band-Aids.