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AI adoption in the enterprise 2020

O'Reilly on Data

More than half of respondent organizations identify as “mature” adopters of AI technologies: that is, they’re using AI for analysis or in production. Supervised learning is the most popular ML technique among mature AI adopters, while deep learning is the most popular technique among organizations that are still evaluating AI.

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

CIO Business Intelligence

Data is the foundation of innovation, agility and competitive advantage in todays digital economy. As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Data quality is no longer a back-office concern.

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Digital transformation 2025: What’s in, what’s out

CIO Business Intelligence

Regardless of the driver of transformation, your companys culture, leadership, and operating practices must continuously improve to meet the demands of a globally competitive, faster-paced, and technology-enabled world with increasing security and other operational risks.

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From project to product: Architecting the future of enterprise technology

CIO Business Intelligence

They achieve this through models, patterns, and peer review taking complex challenges and breaking them down into understandable components that stakeholders can grasp and discuss. Moving to product-based delivery is a significant cultural change. Most importantly, architects make difficult problems manageable. Shawn McCarthy 3.

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Data & Analytics Maturity Model Workshop Series

Speaker: Dave Mariani, Co-founder & Chief Technology Officer, AtScale; Bob Kelly, Director of Education and Enablement, AtScale

Check out this new instructor-led training workshop series to help advance your organization's data & analytics maturity. Given how data changes fast, there’s a clear need for a measuring stick for data and analytics maturity. Workshop video modules include: Breaking down data silos. Sign up now!

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Why Best-of-Breed is a Better Choice than All-in-One Platforms for Data Science

O'Reilly on Data

So you need to redesign your company’s data infrastructure. That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows. The Two Cultures of Data Tooling. A little of both?

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The unreasonable importance of data preparation

O'Reilly on Data

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. Why is high-quality and accessible data foundational?