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Enterprise-grade ML platform in AWS: A starter kit
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Enterprise-grade ML platform in AWS: A starter kit
NASDAQ CM: GDYN
$18.26
Nov 22, 2024 4:00 PM EST
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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.

Blog posts:

September 02, 2024 Accelerating enterprise data migrations: A GenAI recipe
August 07, 2024 LLMOps blueprint for open-source large language models
February 16, 2024 Machine learning for optimized campaign delivery and performance: A Yieldmo case study
November 10, 2023 A scalable, configuration-driven machine learning platform
October 13, 2023 LLMOps blueprint for closed-source large language models
August 17, 2023 Semantic layer: Design principles and cloud-agnostic architecture
July 20, 2023 Analytics and ML platform modernization: A case study
June 21, 2023 The data estate modernization playbook: Seven steps for business transformation
May 17, 2023 IoT platform: A starter kit for Azure
April 12, 2023 How to enhance MLOps with ML observability features: A guide for AWS users
February 22, 2023 How a Fortune 500 manufacturer reduced time-to-market for industrial tools using a data observability framework
January 19, 2023 Building an IoT platform in GCP: A starter kit
May 10, 2022 Enterprise-grade ML platform in AWS: A starter kit
May 05, 2022 Data quality control framework for enterprise data lakes
April 01, 2022 Grid Dynamics analytics platform for smart manufacturing: A Jabil case study
June 10, 2021 Establishing advanced BI capabilities with Google Looker: A step by step tutorial
January 21, 2021 Deploy Data Platform on AWS in One Day
October 20, 2020 Turn data into insights faster with Grid Dynamics analytics platform starter kit on AWS cloud
October 15, 2020 5 steps to implementing a successful DataOps practice
October 06, 2020 From data lake to analytical data platform
November 14, 2017 Delivering actionable insights in real-time by moving from batch to stream processing: A digital media case study

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

Big Data, Insights / By Dmitry Mezhensky, Nikita Kotov

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

Big Data, Insights / By Dmitry Mezhensky, Nikita Kotov, Denis Shershov

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.