Case Study: eMAG accelerates time to insight with Dremio

eMAG accelerates time to insight and leaves no opportunities uncovered with Dremio

eMAG, the Romanian retail and e-commerce company behind emag.ro, needed a faster way to turn fragmented data into insights as its online business outgrew its IT infrastructure. Reports were arriving too late to be useful, data was siloed across systems like MySQL, SQL Server, Hadoop HDFS, Hive, and Amazon S3, and the manual ETL-heavy process made ad-hoc analysis difficult.

To solve this, eMAG implemented Dremio as its data lake engine and query layer for BI and analytics tools such as Tableau and Qlik. With Dremio, the team can query and join data across sources directly, enabling faster dashboarding, self-service analytics, and better data discovery; report creation dropped from weeks to hours, marketplace KPI analysis fell from 1 day to 20 minutes, and overall report generation time is expected to improve by 50–75%.

eMAG

Laurentiu Matei

BI & ERP Director