Remove AWS Remove Data Lakes Remove Internet of Things
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What Are the Best Data Modeling Methodologies & Processes for My Data Lake?

phData

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

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Generate actionable insights for predictive maintenance management with Amazon Monitron and Amazon Kinesis

AWS Machine Learning Blog

It includes sensor devices to capture vibration and temperature data, a gateway device to securely transfer data to the AWS Cloud, the Amazon Monitron service that analyzes the data for anomalies with ML, and a companion mobile app to track potential failures in your machinery.

AWS 90
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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Machine learning and AI analytics: Machine learning and AI analytics leverage advanced algorithms to automate the analysis of data, discover hidden patterns, and make predictions. IoT analytics: IoT (Internet of Things) analytics deals with data generated by IoT devices, such as sensors, connected appliances, and industrial equipment.

Analytics 203
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Deploy a predictive maintenance solution for airport baggage handling systems with Amazon Lookout for Equipment

AWS Machine Learning Blog

In this post, we describe how AWS Partner Airis Solutions used Amazon Lookout for Equipment , AWS Internet of Things (IoT) services, and CloudRail sensor technologies to provide a state-of-the-art solution to address these challenges. It’s an easy way to run analytics on IoT data to gain accurate insights.

AWS 109
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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning Blog

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

AI 127
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ETL Pipelines With Python Azure Functions

Mlearning.ai

The source and target points can be of any storage service, for instance an Azure Blob Storage container, an AWS S3 bucket or a database system to name a few. A batch ETL works under a predefined schedule in which the data are processed at specific points in time. There are mainly 2 different types of ETL: batch and streaming.

ETL 52
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Generative AI for agriculture: How Agmatix is improving agriculture with Amazon Bedrock

AWS Machine Learning Blog

This post describes how Agmatix uses Amazon Bedrock and AWS fully featured services to enhance the research process and development of higher-yielding seeds and sustainable molecules for global agriculture. AWS generative AI services provide a solution In addition to other AWS services, Agmatix uses Amazon Bedrock to solve these challenges.

AWS 117