Creating a serverless Big Data analyser with Amazon Athena
We used AWS services and the Cloud to visually interpret and analyse Big Data with a cost-effective, fast, and scalable solution.
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Using AWS services and the Cloud, we created a means to visually interpret and analyse Big Data that is cost-effective, fast, and easy to scale.
Our application was designed to meet all of these objectives, for a fully flexible answer to Big Data needs.
- This solution is also very easy to expand thanks to the Cloud
- Can be easily combined with Machine Learning & Artificial Intelligence systems for greater insight
- The final build can handle various types of data to present comparisons and insights
- It also offers visualisation, which helps identify key trends and correlations
Big Data is becoming increasingly relevant for today’s businesses. Companies have access to larger and larger amounts of information, but often lack the means to effectively make use of this.
We developed a solution that’s easy to expand, significantly cheaper than on-premise solutions, and useful across a wide range of large scale data sets. We’ve used variants for multiple clients to meet their unique data needs and challenges. This application can be developed further with Machine Learning systems and Artificial Intelligence for more advanced functions.
Amazon Athena, Data Lake, Serverless, Infrastructure as a Code, Big Data, ETL
Amazon S3 Bucket, AWS Glue, Amazon QuickSight, AWS Lambda, Terraform
1 Developer, 1 DevOps
About the Client
PGS Software is one of the largest public listed custom software & services providers in Poland. As an AWS Advanced Consulting Partner, we specialise in Cloud projects – consulting, cloud-native development, application modernisation, & migration. Working according to agile methodologies (Scrum, DevOps, & Continuous Delivery), we create mobile & web applications as well as provide Business Analysis, Visual Design, UX, UI, & QA services to clients worldwide. We have development & business entities in Poland, UK, Germany, & Spain.
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