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.

video game industry icon
Video games

Video game companies collect huge volumes of data from in-game instrumentation and digital marketing channels. We help them to build data processing infrastructures and pipelines that enable advanced business analytics and data-drive optimization.

Our latest thinking on data and analytics

Turn data into insight faster with Grid Dynamics Analytics Platform Starter Kit on AWS cloud
In this article, we present an Analytics Platform Starter Kit developed by Grid Dynamics in collaboration with AWS. This solution helps to handle increasing volumes, velocities, and varieties of data without sacrificing quality, security, or accessibility.
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Why you need data quality automation to make data-driven decisions with confidence
In this blog post, we review a typical data flow, causes of data corruption, how to set confidence levels, and data quality goals. Lastly, we go under the hood and explain our solution to monitoring data quality in production in real-time.
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Unsupervised real-time anomaly detection
In this article, we present a solution for real-time anomaly detection in system and application metrics. This approach can help to implement automated metric monitoring and alerting in various IT and DevOps use cases.
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Our clients

Finance & Insurance

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