Success Case | Building a Secure and Scalable Data Platform

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Large European insurance company

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The Challenge

An insurance company faced the substantial challenge of creating a centralized Data Lake to streamline automated data ingestion, preprocessing, and transformation processes. This endeavor aimed to produce a mature, secure, and scalable data catalog, facilitating diverse use cases such as training and operationalizing Machine Learning (ML) models, business dashboard/report exploitation, and supporting various company processes. Additionally, the platform needed to incorporate third-party data while ensuring stringent compliance with GDPR and security requirements.

The Solution

Keepler’s solution involved deploying a Secured Data Platform utilizing AWS S3 for primary storage, with AWS Glue Catalog serving as the data catalog backbone. To enhance permission management and security, the implementation of LakeFormation is in progress. The data processing utilized a suite of AWS services, including AWS Glue, Lambda, AWS Batch, EMR, StepFunctions, and Kinesis Firehose.

Security, being paramount, was bolstered through multiple strategies: anonymization of structured and unstructured data, strict access limitations, and adherence to the principle of least privilege. To further enhance security, the entire platform was isolated from the internet, with secured public APIs serving as the sole access points, each fortified with Web Application Firewall (WAF) integration for rigorous authentication.

The Result

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Keepler is a full-stack analytics services company specialized in the design, construction, deployment and operation of advanced public cloud analytics custom-made solutions. We bring to the market the Data Product concept, which is a fully automated, public cloud services-based, tailored software that adds advanced analytics, data engineering, massive data processing, and monitoring features. In addition, we help our customers transition to using public cloud services securely and improve data governance to make the organization more data-centric.

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