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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. They needed IoT sensors, for example, to extract relevant data from the sites.

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

CIO Business Intelligence

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. Kubernetes can align a real-time AI execution strategy for microservices, data, and machine learning models, as it adds dynamic scaling to all of these things.

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

One of the primary drivers for the phenomenal growth in dynamic real-time data analytics today and in the coming decade is the Internet of Things (IoT) and its sibling the Industrial IoT (IIoT). One group has declared , “IoT companies will dominate the 2020s: Prepare your resume!” trillion by 2030. trillion by 2030.”.

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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. Without this, organizations will continue to pay a “bad data tax” as AI/ML models will struggle to get past a proof of concept and ultimately fail to deliver on the hype.

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Employing IoT to Boost Business

TDAN

IoT has a lot more to offer than merely establishing connections between systems and devices. IoT is paving ways for new services and products, which were just a figment of our imagination up until a […].

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