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Experimentation in Data Science

TDAN

Modern business is all about data, and when it comes to increasing your advantage over competitors, there is nothing like experimentation. Experiments in data science are the future of big data. Innovations can now win the future. Already, data scientists are making big leaps forward.

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Large Language Models Take AI World By Storm

David Menninger's Analyst Perspectives

In addition, analytics vendors have been augmenting business intelligence (BI) products with AI. And recently, ChatGPT has raised awareness of AI and instigated research and experimentation into new ways in which AI can be applied. Data-driven organizations need to process data in real time which requires AI.

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CBRE’s Sandeep Davé on accelerating your AI ambitions

CIO Business Intelligence

Sandeep Davé knows the value of experimentation as well as anyone. Davé and his team’s achievements in AI are due in large part to creating opportunities for experimentation — and ensuring those experiments align with CBRE’s business strategy. And those experiments have paid off.

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AI poised to replace entry-level positions at large financial institutions

CIO Business Intelligence

Right now most organizations tend to be in the experimental phases of using the technology to supplement employee tasks, but that is likely to change, and quickly, experts say.

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Top 8 predictive analytics tools compared

CIO Business Intelligence

The tool builds heavily on business intelligence and reporting by treating predictions as just another column in the analytics presentation. A free plan allows experimentation. One of the oldest statistics and business intelligence packages from SAS has grown stronger and more capable with age.

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The early returns on gen AI for software development

CIO Business Intelligence

Software and coding development remain a high-value area for experimentation, in addition to content development and knowledge management, in an effort to boost operational efficiencies,” he says. Junior developers are reporting the biggest productivity boosts, but this remains an area of active research and experimentation,” Tandon says.

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Don’t Blink: You’ll Miss Something Amazing!

Cloudera

Flexible use of compute resources on analytics — which is even more important as we start performing multiple different types of analytics, some critical to daily operations and some more exploratory and experimental in nature, and we don’t want to have resource demands collide.