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Enable business users to analyze large datasets in your data lake with Amazon QuickSight

AWS Big Data

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

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Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

Inventory management is a critical function for any business that deals with physical products. The primary challenge businesses face with inventory management is balancing the cost of holding inventory with the need to ensure that products are available when customers demand them.

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Rocket Mortgage lays foundation for generative AI success

CIO Business Intelligence

That’s why Rocket Mortgage has been a vigorous implementor of machine learning and AI technologies — and why CIO Brian Woodring emphasizes a “human in the loop” AI strategy that will not be pinned down to any one generative AI model. Today, 60% to 70% of Rocket’s workloads run on the cloud, with more than 95% of those workloads in AWS.

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4 ways generative AI addresses manufacturing challenges

IBM Big Data Hub

Or we create a data lake, which quickly degenerates to a data swamp. Additionally, these accelerators are pre-integrated with various cloud AI services and recommend the best LLM (large language model) for their domain. Contextual data understanding Data systems often cause major problems in manufacturing firms.

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What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . But first, let’s define the data mesh design pattern.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

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

CIO Business Intelligence

Credo che il change management sia un tema fondamentale, che ogni CIO deve gestire”, afferma Andrea Roero, Chief information officer di Molteni, gruppo di aziende dell’arredo di design Made in Italy. Dal 2000 l’azienda è una spa, con il Comune di Roma come unico socio.