Blog Tags: AWS
Invisible Threats, Visible Solutions: Integrating AWS Macie and Tiger Data Fabric for Ultimate Security
Data defenses are now fortified against potential breaches with the Tiger Data Fabric-AWS Macie integration, automating sensitive data discovery, evaluation, and protection in the data pipeline for enhanced security. Explore how to integrate AWS Macie into a data fabric.
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How to Design your own Data Lake Framework in AWS
Learn how you can efficiently build a Data Lakehouse with Tiger Data Fabric’s reusable framework. We leverage AWS’s native services and open-source tools in a modular, multi-layered architecture. Explore our insights and core principles to tailor a solution for your unique data challenges.
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Revolutionizing SMB Insurance with AI-led Underwriting Data Prefill Solutions
US SMBs often struggle with complex and time-consuming insurance processes, leading to underinsurance. Tiger Analytics’ AWS-powered prefill solution offers a customizable, accurate, and cost-saving approach. With 95% data accuracy, a 90% fill rate, and potential $10M annual savings, insurers can streamline underwriting, boost risk assessment, and gain a competitive edge.
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REST API with AWS SageMaker: Deploying Custom Machine Learning Models
Learn how to deploy custom Machine Learning (ML) models using AWS SageMaker and REST API. Understand the steps involved, including setting up the environment, training models, and creating endpoints for real-time predictions, as well as why to integrate ML models with REST APIs for scalable deployment.
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Building Data Engineering Solutions: A Step-by-Step Guide with AWS
In this article, delve into the intricacies of an AWS-based Analytics pipeline. Learn to apply this design thinking to tackle similar challenges you might encounter and in order to streamline data workflows.
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