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10 AI Conferences in the USA (2025): Connect with Top AI and Data Minds

Data Science Dojo

According to Statista, the AI industry is expected to grow at an annual rate of 27.67% , reaching a market size of US$826.70bn by 2030. With rapid advancements in machine learning, generative AI, and big data, 2025 is set to be a landmark year for AI discussions, breakthroughs, and collaborations.

AI 294
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Discover the Most Important Fundamentals of Data Engineering

Pickl AI

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

professionals

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Most Common Use Cases of Data Engineering in Healthcare

phData

Data engineering in healthcare is taking a giant leap forward with rapid industrial development. However, data collection and analysis have been commonplace in the healthcare sector for ages. Data Engineering in day-to-day hospital administration can help with better decision-making and patient diagnosis/prognosis.

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Shaping the future: OMRON’s data-driven journey with AWS

AWS Machine Learning Blog

In their Shaping the Future 2030 (SF2030) strategic plan, OMRON aims to address diverse social issues, drive sustainable business growth, transform business models and capabilities, and accelerate digital transformation. About the Authors Emrah Kaya is Data Engineering Manager at Omron Europe and Platform Lead for ODAP Project.

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The Future of Data Science Jobs: Will 2030 Mark Their End?

DataSeries

A career in data science is highly in demand for skilled professionals. There has been growing speculation that by 2030, the role of traditional data scientists might face a significant decline or transformation. This prediction is driven by advancements in technology, automation, and shifts in how businesses utilize data.

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Remove the Barriers from AI Adoption

DataRobot

Yet, PwC Research estimates that AI adoption will produce nearly $16 trillion in business growth by the year 2030. In a 2020 Capgemini Research study, only a meager 13% of businesses had successfully deployed use cases in production and continued to scale the use cases throughout multiple business teams. Process Deficiencies. “AI

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Navigating the 2024 Data Analyst career growth landscape

Pickl AI

Cloud-based Data Analytics Utilising cloud platforms for scalable analysis. billion 22.32% by 2030 Automated Data Analysis Impact of automation tools on traditional roles. by 2030 Real-time Data Analysis Need for instant insights in a fast-paced environment. billion Value by 2030 – $125.64