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IoT Data Governance: Taming the Deluge in Connected Environments

Dataversity

The Internet of Things (IoT) has rapidly redefined many aspects of our lives, permeating everywhere from our jobs to our homes and every space in between. However, the sheer volume and complexity of data generated by an ever-growing network of connected devices presents unprecedented challenges.

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Building Trust in the Digital Age: The Role of Data Verification

Dataversity

Data has famously been referred to as the “new oil,” powering the fifth industrial revolution. As our reliance on data-intensive sectors like finance, healthcare, and the Internet of Things (IoT) grows, the question of trust becomes paramount.

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Connected products at the edge

IBM Journey to AI blog

There are many overlapping business usage scenarios involving both the disciplines of the Internet of Things (IoT) and edge computing. This use case involves devices and equipment embedded with sensors, software and connectivity that exchange data with other products, operators or environments in real-time.

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Data lakes vs. data warehouses: Decoding the data storage debate

Data Science Dojo

By using this method, you may speed up the process of defining data structures, schema, and transformations while scaling to any size of data. Through data crawling, cataloguing, and indexing, they also enable you to know what data is in the lake. It may be easily evaluated for any purpose.

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The Crucial Role of Data Lifecycle Management in Driving Business Success

Dataversity

No matter what industry you work in, Data Management is increasingly important for your career and performance. Information is no longer separate bits of data – the internet of things (IoT) and big data mean that every piece of data is interconnected.

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1

AWS Machine Learning Blog

This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. In recent years, this new learning paradigm has been successfully adopted to address the concern of data governance in training ML models. This allows you to train an ML model on distributed data, without the need to share or move it.

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Why the Next Generation of Data Management Begins with Data Fabrics

Dataversity

However, most enterprises are hampered by data strategies that leave teams flat-footed when […]. The post Why the Next Generation of Data Management Begins with Data Fabrics appeared first on DATAVERSITY. Click to learn more about author Kendall Clark. The mandate for IT to deliver business value has never been stronger.