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Research 360 Solutions on AWS is a comprehensive toolset designed to simplify the intricate data management process for researchers. These solutions provide curated, streamlined options for handling all steps of the data pipeline, from data identification to sharing findings. Offering a consistent and efficient experience, it aims to reduce complexity and enhance productivity at every step of your research journey.

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Predictive maintenance and reliability engineering are essential for smooth manufacturing operations. Our solution streamlines every phase of the manufacturing lifecycle—from design to sustainability—using cutting-edge technologies like IoT, AI, and digital twins. This suite enhances efficiency, reduces waste, and drives smarter manufacturing decisions. Leveraging Industrial Data Fabric on AWS, operations leaders can predict equipment failures, optimize maintenance schedules, and enhance asset reliability. By integrating data from various sources, this solution empowers predictive maintenance and reliability initiatives across all stages, ensuring sustainable and resilient production processes. ATTENTION MONITRON CUSTOMERS: Amazon Monitron will no longer be available to new customers effective October 31, 2024. If you're impacted, please scroll down to the support section or reach out to leverage our Amazon Monitron Transition Plan, offered at no cost to you.

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Deploy a cloud foundation to support highly-regulated workloads and complex compliance requirements based on AWS Well Architected best practices

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Embark on your journey with our AWS Jumpstart Program! Designed specifically for startups and nimble enterprise teams, this program offers valuable resources in areas such as Analytics (AWS Data Exchange, Amazon Redshift, Amazon QuickSight, etc.), Internet of Things (AWS IoT SiteWise, AWS IoT Analytics, AWS Greengrass, etc.), Machine Learning (Amazon SageMaker, Amazon Comprehend, Amazon Textract, etc.), Containers (Amazon ECS, Amazon EKS, Fargate), and Non-relational Databases (Amazon DynamoDB, Amazon DocumentDB, Amazon ElasticSearch Service, etc.). Get prescriptive guidance and implementation support depending on your project requirements.

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Integrate data sources and present data insights in a clear and user-friendly way. Data-Driven Insights solutions provide the information you need to proactively diagnose issues, identify trends, and enable growth.

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Our Interactive Data Insights Suite offers robust tools for advanced data visualization, reporting, and analysis. Designed for speed and simplicity, these tools allow you to interpret and communicate complex data insights swiftly and efficiently, often with no coding required. With the ability to generate dynamic graphics and interactive dashboards, construct comprehensive reports to monitor KPIs, and carry out detailed data analysis, our product empowers you to understand your data profoundly and share insights effectively.

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CI/CD pipeline is where new code is submitted on one end, tested over a series of stages (source, build, test, staging, and production), and then published as production-ready code. Each stage of the CI/CD pipeline is structured as a logical unit in the delivery process. Each stage acts as a gate that vets a certain aspect of the code. As the code progresses through the pipeline, the assumption is that the quality of the code is higher in the later stages, because more aspects of it continue to be verified. Problems uncovered in an early stage stop the code from progressing through the pipeline. Results from the tests are immediately sent to the team, and all further builds and releases are stopped if software does not pass the stage. We bring in a complete set of CI/CD developer tools to accelerate software development and release cycles. This enables the rapid and reliable delivery of features and updates.

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Amazon SageMaker JumpStart offers over 350 built-in algorithms, pre-trained models, and pre-built solution templates to help you get started with ML fast. JumpStart provides one-click access to a wide variety of pre-trained models for common ML tasks such as object detection, text classification, summarization, text generation and much more.