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Innovative data integration in 2024: Pioneering the future of data integration

CIO

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly Media - Ideas

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. You can find full results from the survey in the free report “Evolving Data Infrastructure”.). Data Platforms.

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How Industry 4.0 Changes Predictive Maintenance From Mobile Apps And What It Means For The Future ?

OTS Solutions

has been transforming the manufacturing sector through the integration of advanced technologies such as artificial intelligence, the Internet of Things, and big data analytics. These technologies allow mobile apps to learn and adapt to specific equipment conditions, further reducing the risk of equipment failures. Industry 4.0

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.

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Unlocking the Power of AI with a Real-Time Data Strategy

CIO

Titanium Intelligent Solutions, a global SaaS IoT organization, even saved one customer over 15% in energy costs across 50 distribution centers , thanks in large part to AI. AI is the perception, synthesis, and inference of information by machines, to accomplish tasks that historically have required human intelligence.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

Altexsoft

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. Who needs a data lake? Data warehouse vs. data lake in a nutshell.

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Building an Open Data Processing Pipeline for IoT

Cloudera

Last week Cloudera introduced an open end-to-end architecture for IoT and the different components needed to help satisfy today’s enterprise needs regarding operational technology (OT), information technology (IT), data analytics and machine learning (ML), along with modern and traditional application development, deployment, and integration.

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