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AI & the enterprise: protect your data, protect your enterprise value

CIO

The premise was that enterprises needed to secure their critical data more stringently in the wake of data hacks and emerging AI processes. I wrote, “ It may be even more important for the security team to protect and maintain the integrity of proprietary data to generate true, long-term enterprise value. Years later, here we are.

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10 most in-demand enterprise IT skills

CIO

The software and services an organization chooses to fuel the enterprise can make or break its overall success. Here are the 10 enterprise technology skills that are the most in-demand right now and how stiff the competition may be based on the number of available candidates with resume skills listings to match.

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Are enterprises ready to adopt AI at scale?

CIO

To overcome those challenges and successfully scale AI enterprise-wide, organizations must create a modern data architecture leveraging a mix of technologies, capabilities, and approaches including data lakehouses, data fabric, and data mesh. To learn more about how enterprises can prepare their environments for AI , click here.

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Unlocking the full potential of enterprise AI

CIO

1] The limits of siloed AI implementations According to SS&C Blue Prism , an expert on AI and automation, the chief issue is that enterprises often implement AI in siloes. SS&C Blue Prism argues that combining AI tools with automation is essential to transforming operations and redefining how work is performed.

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5 Things a Data Scientist Can Do to Stay Current

And more is being asked of data scientists as companies look to implement artificial intelligence (AI) and machine learning technologies into key operations. Fostering collaboration between DevOps and machine learning operations (MLOps) teams. Sharing data with trusted partners and suppliers to ensure top value.

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From Machine Learning to AI: Simplifying the Path to Enterprise Intelligence

Cloudera

As the AI landscape evolves from experiments into strategic, enterprise-wide initiatives, its clear that our naming should reflect that shift. Thats why were moving from Cloudera Machine Learning to Cloudera AI. Its a signal that were fully embracing the future of enterprise intelligence. Ready to learn more?

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Leveraging AMPs for machine learning

CIO

Such a large-scale reliance on third-party AI solutions creates risk for modern enterprises. Data scientists and AI engineers have so many variables to consider across the machine learning (ML) lifecycle to prevent models from degrading over time. However, the road to AI victory can be bumpy.

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The Business Value of MLOps

As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models. Download the report to find out: How enterprises in various industries are using MLOps capabilities.

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ERP Migration: Why Data Quality Comes First

Automation and machine learning are augmenting human intelligence, tasks, jobs, and changing the systems that organizations need in order not just to compete, but to function effectively and securely in the modern world. ERP (Enterprise Resource Planning) system migration is a case in point.