Remove Digital Transformation Remove Internet of Things Remove Modeling
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Editorial Review of “Building Industrial Digital Twins”

Rocket-Powered Data Science

I was asked by the publisher to provide an editorial review of the book “Building Industrial Digital Twins: Design, develop, and deploy digital twin solutions for real-world industries using Azure Digital Twins“, by Shyam Varan Nath and Pieter van Schalkwyk. The digital twin is more than a data collector. Let us begin….

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

One of the primary drivers for the phenomenal growth in dynamic real-time data analytics today and in the coming decade is the Internet of Things (IoT) and its sibling the Industrial IoT (IIoT). Now things are the Internet.”. trillion by 2030. RFID), inventory monitoring (SKU / UPC tracking).

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What is data architecture? A framework to manage data

CIO Business Intelligence

Its an offshoot of enterprise architecture that comprises the models, policies, rules, and standards that govern the collection, storage, arrangement, integration, and use of data in organizations. Many organizations today are looking to modernize their data architecture as a foundation to fully leverage AI and enable digital transformation.

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Unlocking value: Top digital transformation trends

IBM Big Data Hub

While digital transformation has been a trend for some years, emerging technologies have made this movement even more important. Companies are rethinking their business models to become more digital and competitive. Digital transformation is an important component of a modern organization’s business operations.

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Digital transformation examples

IBM Big Data Hub

A digital transformation is an overhauled, digital-first approach to how a business is run. The digital world is evolving quickly with new products and digital technologies that require vigorous digital transformation initiatives. Why digital transformation?

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase. MLOps “done right” addresses sustainable model operations, explainability, trust, versioning, reproducibility, training updates, and governance (i.e.,

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Recently, EUROGATE has developed a digital twin for its container terminal Hamburg (CTH), generating millions of data points every second from Internet of Things (IoT)devices attached to its container handling equipment (CHE).

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