Data and analytics

Incorporate advanced analytics, data science, and AI throughout your enterprise using cloud data platforms.

Grid Dynamics helps technology and analytics leaders design and build powerful infrastructures for a data-driven enterprise:

  • Run data processing and analytics in the cloud
  • Process billions of events in real time
  • Provide self-service analytics to all organizations
  • Provide advanced toolkits to your data science teams
  • Enable AI productization using MLOps
  • Data platforms

    Data engineering and analytics are now mission-critical components in virtually all industries: reporting, insights, and optimization of business decisions all critically depend on the data infrastructure.

    Modern data platforms include many features and services ranging from elastic storage and computing to metadata discovery and anomaly detection in data. We have built data platforms and services for many Fortune 500 companies, as well as smaller clients, and we offer world-class expertise, engineering skills, and detailed solution blueprints in this area.

  • Real-time analytics

    In-stream aggregation is an indispensable tool for applications that require processing an extremely large number of events or provide business users with near real-time reporting. We develop in-stream and real-time data solutions for the largest technology, media, and advertising companies offering unique expertise in building fault-tolerant, scalable, and performant pipelines using Spark, Kafka, Flink, Beam, and cloud-native technologies.

  • Self-Service data and analytics

    Although data engineering, ad hoc analytics, and data science technologies are widely adopted in multiple industries, many companies struggle to make these capabilities available to all teams and organizations who need them. We help to remove barriers and build self-service solutions that require minimal engineering support and reduce the gap between prototyping and productization.

  • AI and decision automation

    Data platforms and self-service capabilities provide a foundation for improving business performance using data-driven methods, but actual data commercialization is a separate challenge that requires considerable domain expertise and data science skills. We specialize in optimizing marketing, supply chain, and other enterprise operations using AI/ML methods and help our clients to build these capabilities on top of generic data processing and analytics infrastructure.

We develop data platforms and analytic tools for many companies in retail, telecom, video games, finance, and other industries.

Our clients


We provide flexible engagement options to design and build a customer intelligence and analytics solution for your enterprise. Contact us today to start with a workshop, discovery, or POC.


We offer free workshops with our top experts to discuss your challenges, potential areas of improvement, and industry best practices.

Proof of concept

If you have already identified a specific use case that can be solved using data science and other customer intelligence technologies, we usually can start with a 4–8 week proof-of-concept project to deliver tangible results for your enterprise.


If you are in the stage of requirements analysis and strategy development, we can start with a 2–3 week discovery phase to identify right use cases for customer intelligence and personalization, design your solution using industry best practices, and build an implementation roadmap.