Remove 2012 Remove AWS Remove Business Intelligence
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Architecture to AWS CloudFormation code using Anthropic’s Claude 3 on Amazon Bedrock

AWS Machine Learning Blog

We can also gain an understanding of data presented in charts and graphs by asking questions related to business intelligence (BI) tasks, such as “What is the sales trend for 2023 for company A in the enterprise market?” AWS Fargate is the compute engine for web application.

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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning Blog

Reduced operational overhead – The EMR Serverless integration with AWS streamlines big data processing by managing the underlying infrastructure, freeing up your team’s time and resources. Runtime roles are AWS Identity and Access Management (IAM) roles that you can specify when submitting a job or query to an EMR Serverless application.

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MLOps for IoT Edge Ecosystems: Building an MLOps Environment on AWS

The MLOps Blog

This can enable the company to leverage the data generated by its IoT edge devices to drive business decisions and gain a competitive advantage. AWS offers a three-layered machine learning stack to choose from based on your skill set and team’s requirements for implementing workloads to execute machine learning tasks.

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Publish predictive dashboards in Amazon QuickSight using ML predictions from Amazon SageMaker Canvas

AWS Machine Learning Blog

Business analysts play a pivotal role in facilitating data-driven business decisions through activities such as the visualization of business metrics and the prediction of future events. Then we detail how to build a model and run predictions, and demonstrate the business analyst experience. Choose Create policy.

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How to choose a graph database: we compare 6 favorites

Cambridge Intelligence

OLAP is better for complex analysis across a wider, but more static, set of data, like business intelligence and knowledge graph analysis. Part of AWS – with high availability worldwide and easy integration with the rest of AWS’ products. Here, performance for writing to the database is important.

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Process Mining – Ist Celonis wirklich so gut? Ein Praxisbericht.

Data Science Blog

Dabei arbeiten wir technologie-offen und mit nahezu allen Tools – Und oft in enger Verbindung mit Initiativen der Business Intelligence und Data Science. in Databricks oder den KI-Tools von Google, AWS und Mircosoft Azure (Azure Cognitive Services, Azure Machine Learning etc.). Es gab noch einige mehr. Hier fällt mir z.