Tag: Amazon Athena
Enhance conversational AI with advanced routing techniques with Amazon Bedrock | Amazon Web Services
Conversational artificial intelligence (AI) assistants are engineered to provide precise, real-time responses through intelligent routing of queries to the most suitable AI functions. With...
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Supercharge your AI team with Amazon SageMaker Studio: A comprehensive view of Deutsche Bahn’s AI platform transformation | Amazon Web Services
AI’s growing influence in large organizations brings crucial challenges in managing AI platforms. These include developing a scalable and operationally efficient platform that adheres...
Build a robust text-to-SQL solution generating complex queries, self-correcting, and querying diverse data sources | Amazon Web Services
Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL...
Build a robust text-to-SQL solution generating complex queries, self-correcting, and querying diverse data sources | Amazon Web Services
Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL...
Detect anomalies in manufacturing data using Amazon SageMaker Canvas | Amazon Web Services
With the use of cloud computing, big data and machine learning (ML) tools like Amazon Athena or Amazon SageMaker have become available and useable...
Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock | Amazon Web Services
Enterprises are seeking to quickly unlock the potential of generative AI by providing access to foundation models (FMs) to different lines of business (LOBs)....
Modernizing data science lifecycle management with AWS and Wipro | Amazon Web Services
This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination...
Identify cybersecurity anomalies in your Amazon Security Lake data using Amazon SageMaker | Amazon Web Services
Customers are faced with increasing security threats and vulnerabilities across infrastructure and application resources as their digital footprint has expanded and the business impact...
Streamlining ETL data processing at Talent.com with Amazon SageMaker | Amazon Web Services
This post is co-authored by Anatoly Khomenko, Machine Learning Engineer, and Abdenour Bezzouh, Chief Technology Officer at Talent.com. Established in 2011, Talent.com aggregates paid...
Accelerate data preparation for ML in Amazon SageMaker Canvas | Amazon Web Services
Data preparation is a crucial step in any machine learning (ML) workflow, yet it often involves tedious and time-consuming tasks. Amazon SageMaker Canvas now...
Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio | Amazon Web Services
This post is co-written with Marc Neumann, Amor Steinberg and Marinus Krommenhoek from BMW Group. The BMW Group – headquartered in Munich, Germany –...
Build well-architected IDP solutions with a custom lens – Part 5: Cost optimization | Amazon Web Services
Building a production-ready solution in the cloud involves a series of trade-off between resources, time, customer expectation, and business outcome. The AWS Well-Architected Framework...
Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights | Amazon Web Services
An established financial services firm with over 140 years in business, Principal is a global investment management leader and serves more than 62 million...
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