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Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

Such a solution should use the latest technologies, including Internet of Things (IoT) sensors, cloud computing, and machine learning (ML), to provide accurate, timely, and actionable data. Data ingestion and storage Retail businesses have event-driven data that requires action from downstream processes.

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Digital transformation: nei progetti a tutto campo la chiave è il change management

CIO Business Intelligence

Trasformazione digitale: la data platform e il digital twin AMA è tra le organizzazioni che stando imprimendo un forte slancio alla loro digitalizzazione. Roero ha in mente anche l’introduzione dell’intelligenza artificiale per rendere più fluidi e controllati i processi e rendere l’azienda data-driven.

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How to Drive Competitive Advantage from Next-Gen Computing

CIO Business Intelligence

First came those driven by cloud, mobile, and advanced security. Then came the arrival of 5G, edge, and the Internet of Things (IoT). But it also introduces a new set of challenges for the enterprise’s IT infrastructure, not least the need for more powerful tools to process workloads and data faster and more efficiently.

IoT 80
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How to Drive Competitive Advantage from Next-Gen Computing

CIO Business Intelligence

First came those driven by cloud, mobile, and advanced security. Then came the arrival of 5G, edge, and the Internet of Things (IoT). But it also introduces a new set of challenges for the enterprise’s IT infrastructure, not least the need for more powerful tools to process workloads and data faster and more efficiently.

IoT 80
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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. ML model interpretability and data visualization. back to the structure of the dataset.

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The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

During this period, those working for each city’s Organising Committee for the Olympic Games (OCOG) collect a huge amount of data about the planning and delivery of the Games. At the Information, Knowledge, and Games Learning (IKL) unit, we anticipate collecting about 1TB of data from primary sources.