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Building Quick, Robust, and Flexible APIs with Data Virtualization

Data Virtualization

Bring any data to any data consumer, simply and easily: that’s the goal of data virtualization. Yet contrary to what may first come to mind, data consumers are more than simply BI, analytics, or data science applications. Just about every.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

While AGI remains theoretical, organizations can take proactive steps to prepare for its arrival by building a robust data infrastructure and fostering a collaborative environment where humans and AI work together seamlessly. Imagine a self-driving car piloted by an AGI.

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Automate deployment of an Amazon QuickSight analysis connecting to an Amazon Redshift data warehouse with an AWS CloudFormation template

AWS Big Data

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

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12 Cloud Computing Risks & Challenges Businesses Are Facing In These Days

datapine

It provides better data storage, data security, flexibility, improved organizational visibility, smoother processes, extra data intelligence, increased collaboration between employees, and changes the workflow of small businesses and large enterprises to help them make better decisions while decreasing costs.

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Public cloud vs. private cloud vs. hybrid cloud: What’s the difference?

IBM Big Data Hub

This infrastructure model relies on a network of remote data centers , servers and storage systems owned and operated by a third-party service provider. This infrastructure model relies on a network of remote data centers , servers and storage systems owned and operated by a third-party service provider. What is cloud computing?

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How Financial Services and Insurance Streamline AI Initiatives with a Hybrid Data Platform

Cloudera

There’s also the risk of various forms of data leakage, including intellectual property (IP) as well as personally identifiable information (PII) especially with commercial AI solutions. It’s the most revolutionary technological development in at least a generation. But it’s also fraught with risk.

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Think inside the box: Container use cases, examples and applications

IBM Big Data Hub

This is done through a form of operating system (OS) virtualization in which features of the OS kernel (e.g., An even larger group of respondents (64%) reported expecting to use containers for at least 50% of the apps they would build over the next 2 years. Containers are all about distributing and protecting data and running apps.