The business opportunity: Integrating new data sources (web and browsing behavior) provided by their partners, which with proper integration would allow them to put forward offers aligned with their user's interests.
The task: Incorporate new data and identify patterns to improve understanding of customer's users and increase Click Through Rate.
Outcome: Designed and implemented a Hadoop-based platform for storing billions of profiles. Conducted an analysis of search patterns in browsing histories to identify users with high probability to convert. Built facility for on-demand data analysis. Created reports set for downstream consumers.
Leading telecom provider
The business opportunity: Operational reporting were both time consuming and prone to errors due to the high number of distributed data sources. Substantial employee effort, the high risk of error and the significant time lag between when the data arrived and when reports were produced, negatively impacted the business.
The task: Create a timely and accurate reporting system to provide insight for improved business operations.
Outcome: Designed and implemented a Hadoop/Hive-based data warehouse for historical and ongoing call records. Cleaned up, enriched, and prepared the data for exploration and visualization.
Digital ad agency
The business opportunity: One of biggest headaches for advertisers on the Internet is fake traffic. A robot "sees" an impression but "it" definitely won't buy anything, wasting advertisers' money. These robots are a problem and having timely identification of fraudulent impressions significantly increases ad efficiency.
The task: Architect an In-Stream Processing Engine in order to detect and eliminate false impressions in real time.
Outcome: We designed and deployed In-Stream Processing infrastructure and then implemented models, designed by a customer's Data Science team, at-scale. Millions of events per second were handled by the resulting solution.
Data management company
The business opportunity: Collect online information from a broad partnership network, correlate and analyze same in order to build user profiles in order to allow retailers, advertisers and other digital companies to deliver relevant customer experiences.
The task: Rearchitect a private data center for integration to the cloud. To enable integration, scalability and future-proof the platform.
Outcome: Data processing pipeline was split into several phases, the first one responsible for the initial data collection from different sources and integration was moved to the cloud infrastructure. This project has cloud enabled future phases of the data processing pipeline.