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The Race For Data Quality in a Medallion Architecture

DataKitchen

For instance, suppose a new dataset from an IoT device is meant to be ingested daily into the Bronze layer. Similarly, downstream business metrics in the Gold layer may appear skewed due to missing segments, which can impact high-stakes decisions. Still, due to connectivity issues or file format mismatches, the load fails.

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Optimizing the IoT Infrastructure for Enhanced Big Data Performance

Smart Data Collective

According to a report by Gartner, the economic impact of all products connected to the IoT will exceed $300 billion by next year. A number of factors are contributing to the proliferation of the IoT. Big data is the foundation of the IoT. Here are some reasons that big data advances will improve the IoT.

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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). Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data.

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

The Edge-to-Cloud architectures are responding to the growth of IoT sensors and devices everywhere, whose deployments are boosted by 5G capabilities that are now helping to significantly reduce data-to-action latency. 5) The emergence of Edge-to-Cloud architectures clearly began pushing Industry 4.0 will look like).

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How the Internet of Things and AI will Transform Sports Business?

Smart Data Collective

In this article, we are going to look into the two advanced technologies – IoT and AI which have brought some tremendous changes to the sports sector. However, limitations with standard analytical models t can keep them from assessing and recording those metrics. Role of IoT in bettering the sports domain.

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The DataOps Vendor Landscape, 2021

DataKitchen

A complete DataOps program will have a unified, system-wide view of process metrics using a common data store. Hitachi Vantara – Digital operations, infrastructure solutions, IOT applications, data management, and multi-cloud acceleration. XenonStack — DataOps, DevOps, decision support, big-data analytics, and IoT services.

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A 5D model to assess your IoT readiness

Cloudera

The number one challenge that enterprises struggle with their IoT implementation is not being able to measure if they are successful or not with it. Most of the enterprises start an IoT initiative without assessing their potential prior hand to be able to complete it. Each metric is associated with one or more questions.

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