Dmitry Mezhensky

Dmitry Mezhensky

Dmitry Mezhensky joined Grid Dynamics in 2014 and has worked on various Big Data projects since. One of the major projects, iCrossing, was a huge success as we built a high-performing Big Data platform. Dmitry is currently on-site at a large retailer.

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Dmitry Mezhensky

Dmitry Mezhensky joined Grid Dynamics in 2014 and has worked on various Big Data projects since. One of the major projects, iCrossing, was a huge success as we built a high-performing Big Data platform. Dmitry is currently on-site at a large retailer.

Dmitry Mezhensky

Enterprise-grade ML platform in AWS: A starter kit

Grid Dynamics has developed an ML Platform Starter Kit for AWS that provides a reference architecture and capabilities for building an ML platform, including an experimentation pipeline, automated CI pipeline, and continuous deployment and serving infrastructure management. The platform utilizes AWS SageMaker and MLflow for model development, training, and serving, and includes CI/CD automation and a model serving layer built on top of Kubernetes and SageMaker.

Data quality control framework for enterprise data lakes

Data quality control is a critical capability for businesses, as data quality issues can disrupt processes, invalidate analytics, and damage a company’s reputation. However, data quality control is often undervalued, and there is room for improvement in most enterprises. Grid Dynamics has developed a scalable and easy-to-extend data quality control framework that integrates with various data sources, performs data quality checks, and visualizes the results using open-source tools like Soda SQL, Kibana, and Apache Airflow.