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Drowning in Data? A Data Lake May Be Your Lifesaver

ODSC - Open Data Science

Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. But, the amount of data companies must manage is growing at a staggering rate. and various countries in Europe.

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A Comprehensive Guide to the main components of Big Data

Pickl AI

Introduction In today’s digital age, the volume of data generated is staggering. According to a report by Statista, the global data sphere is expected to reach 180 zettabytes by 2025 , a significant increase from 33 zettabytes in 2018. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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A Comprehensive Guide to the Main Components of Big Data

Pickl AI

Introduction In today’s digital age, the volume of data generated is staggering. According to a report by Statista, the global data sphere is expected to reach 180 zettabytes by 2025 , a significant increase from 33 zettabytes in 2018. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

The quality and quantity of data can make or break AI success, and organizations that effectively harness and manage their data will reap the most benefits. Data is exploding, both in volume and in variety. With the right data, you can create a data-driven organization that drives business value and innovation.

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The Top AI Slides from ODSC West 2024

ODSC - Open Data Science

Dimensional Data Modeling in the Modern Era by Dustin Dorsey Slides Dustin Dorsey’s AI slides explored the evolution of dimensional data modeling, a staple in data warehousing and business intelligence. Register now while tickets are still 75% off!

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How data stores and governance impact your AI initiatives

IBM Journey to AI blog

AI-optimized data stores enable cost-effective AI workload scalability AI models rely on secure access to trustworthy data, but organizations seeking to deploy and scale these models face an increasingly large and complicated data landscape.

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