Data and analytics

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.

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.

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.

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.