Data science model
for user-generated data

About the Customer

The customer is a global company that focuses on delivering insights about worldwide audiences through collecting and analyzing huge amounts of information.


As a key player in audience insights, the customer needed to develop a data science model that could pull data together, consolidate it, and detect discrepancies.


Exadel’s development team transformed vast amounts of data into a data science model to provide the customer with user data analytics locally and globally. For the model to work properly, Exadel also needed to refactor existing code.

Consequently, Exadel built a major data processing pipeline using cutting-edge technologies such as AWS EMR, AWS S3, AWS Lambda, Spark/Scala, and Apache Airflow. This allowed Exadel to parse, collect, and filter data, which can then be used to create other projects or generate valuable reports.

The solution Exadel developed also allowed the customer to access the results in specialized files that can be used for further analysis and new business opportunities.


With Exadel’s help, the customer can now analyze and compare deviations in user and provider data. The data science model that Exadel built empowers businesses with an audience insights platform to help these companies come up with better content to meet the needs of end users.