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You can't burn data

Jeffrey Phillips

As the concept of digital transformation takes root, you may frequently hear comparisons between data and oil. This comparison was strong enough to lead Wired magazine to define data as the new oil in a magazine article some years ago. Both data and oil are commodities, and exist to some degree in large volumes.

Data 157
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The planning out of this Composable Innovation Enterprise Framework

Paul Hobcraft

Undertaking the initial structure, design, and framing of a Composable Innovation Enterprise Framework typically involves a collaborative effort involving various organizational stakeholders. They can provide insights into technological capabilities, data management, and integration requirements.

Agile 130
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How Data Collaboration Platforms Can Help Companies Build Better AI

Harvard Business Review

There are three immediate challenges for companies that want to train fine-tuned AI models: 1) they require extensive, high-quality data — a scarce resource for many enterprises, 2) third-party AI models can include problematic biases, and 3) training fine-tuned models with users’ personal data may result in privacy violations.

Data 130
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Innovating at Olympic Levels by Embracing Data-Driven Development for You and Your Enterprise

IdeaScale

As the world eagerly awaits the upcoming Paris Olympics, the stage is set for athletes to showcase their preparation, prowess, and determination to clinch the coveted gold medals.

Data 130
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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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The Final Perspective: A Composable Innovation Enterprise Framework

Paul Hobcraft

Are we leveraging Artificial Intelligence (AI) or Machine Learning enough from the explosion of data to identify patterns and insights leading to emerging concept creation? So why did I name this “A composable innovation enterprise framework ? Are we leveraging fully what is available to us to build better innovation concepts?

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The Day the Enterprise Stood Still

PlanBox Innovation

Indeed, in this age of relentless change, the last thing any enterprise wants is a free-falling portfolio of innovative projects. Enhanced Resource Forecasting: It emphasizes data-driven decision-making, enabling the PMO to forecast resource needs, minimizing budget overruns. Oh, the horror! times faster than their counterparts.

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5 Early Indicators Your Embedded Analytics Will Fail

Many application teams leave embedded analytics to languish until something—an unhappy customer, plummeting revenue, a spike in customer churn—demands change. But by then, it may be too late. In this White Paper, Logi Analytics has identified 5 tell-tale signs your project is moving from “nice to have” to “needed yesterday.".

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Drive GTM Efficiency with Tech Stack Consolidation

Consolidating your tech stack is an effective cost-saving measure that drives GTM efficiency and adds value to your enterprise. With a cohesive, integrated tech stack, your revenue teams can deliver an excellent customer experience that sets you up to win faster than your competitors.

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AR/VR Simulations for Sustainable, Regenerative, Circular Cities

Speaker: Nik Gowing, Brenda Laurel, Sheridan Tatsuno, Archie Kasnet, and Bruce Armstrong Taylor

In this session, participants will see how science data from such sources as NASA and NOAA, combined with local data inputs, can be used to both exponentially improve and accelerate net-zero carbon, climate positive and regenerative outcomes.