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Data privacy examples

IBM Big Data Hub

These are just some examples of how organizations support data privacy , the principle that people should have control of their personal data, including who can see it, who can collect it, and how it can be used. For example, they can decline to have their data shared with third parties while allowing the app to generate personalized offers.

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Examples and uses of GIS

IBM Big Data Hub

For example, planners in fire-prone California use tools that incorporate remote sensing, vector data and satellite images to formulate disaster response plans and optimal placement of fire hydrants. Explore the IBM Environmental Intelligence Suite The post Examples and uses of GIS appeared first on IBM Blog.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

Regardless, these are examples of narrow AI. The majority (72%) of enterprises that use APIs for model access use models hosted on their cloud service providers. AGI examples However, once theoretical AGI achieves the above to become actual AGI, its potential applications are vast.

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Business process reengineering (BPR) examples

IBM Big Data Hub

BPR examples are not one-time projects, but rather examples of a continuous journey of innovation and change focused on optimizing end-to-end processes and eliminating redundancies. This blog outlines some BPR examples that benefit from a BPM methodology.

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Partner Webinar: A Framework for Building Data Mesh Architecture

Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri

Yet they are continually challenged with providing access to all of their data across business units, regions, and cloud environments. In this session, you will learn: How the silos development led to challenges with data growth, data quality, data sharing, and data governance (an example of datamesh paradigm adoption).

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IBM Cloud delivers enterprise sovereign cloud capabilities

IBM Big Data Hub

As we see enterprises increasingly face geographic requirements around sovereignty, IBM Cloud® is committed to helping clients navigate beyond the complexity so they can drive true transformation with innovative hybrid cloud technologies. We believe this is particularly important with the rise of generative AI.

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Migrating data to the cloud? Don’t neglect change management

Collibra

1 For data professionals embarking on a data cloud migration , the stakes couldn’t be any higher. It’s why effective change management is not just a luxury; it’s a necessity for unlocking the full power of cloud capabilities and ensuring adoption. Ready to be a cloud data migration hero ? The challenges are real.

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