Remove 2030 Remove Data Management Remove Innovation
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AstraZeneca’s Axial Transformation: A Digital Backbone for Innovation

Timo Elliott

Serving millions of patients annually, AstraZenecas commitment to sustainability and growth through innovation underpins its ambitious vision to pioneer advancements in healthcare and improve lives worldwide. An example of an end-to-end process flow as part of the Axial transformation project.

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BFSI: Banking, Financial Services and Insurance

The BAWorld

from 2023 to 2030. Organizations of the BFSI sector help to enhance the possibility of the accumulation and circulation of capital, granting business owners to expand their businesses, and giving individuals the possibility to manage their finances properly. 4 billion by 2030. 3 trillion in premiums ( Source: Statista ).

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How AI is Changing the Data Integration Process 

Astera

The Explosion in Data Volume and the Need for AI The global AI market today stands at $100 billion and is expected to grow 20-fold up to nearly two trillion dollars by 2030. This massive growth has a spillover effect on various areas, including data management.

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The success of your AI strategy depends on building these 5 competencies

Astera

trillion yearly to the global economy by 2030; thats more than the current output of China and India combined. This means that your AI strategy should not only include foundational AI capabilities like cloud platforms, data platforms, architecture, and governance but also encompass C-suite buy-in, innovation culture, etc.,

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Future economy: personal and corporate strategies for the age of AI, climate crisis, and aging…

Analysts Corner

flexible grippers and tactile arrays that can improve handling of varied objects); substantial investments in data management and governance; the development of new types of hardware (e.g., The World Health Organization (WHO) estimates a deficit of 10 million healthcare workers by 2030.

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Understanding AI Agents: A Beginner’s Guide

Domo

billion by 2030. Organizations use AI agents to boost operational efficiency by analyzing data in real time and automating routine tasks. These generative AI agents use your organizations data to provide instant analysis, saving your team valuable time and reducing costs. billion in 2024 to $47.1