N11 - Oredata
Success Study Detail Background

{SCALABLE, REAL-TIME DATA ANALYTICS PLATFORM}

N11

Oredata implemented an end-to-end big data and analytics pipeline for N11.com to analyze their customer market behavior data. Oredata developed the solution by using serverless Google Cloud products to scale automatically.

ABOUT N11

Doğuş Planet was established in June 2012 in partnership with Doğuş Group and SK Group, one of the biggest groups in South Korea, to operate in the e-commerce sector. Within the framework of this strong partnership, Doğuş Planet, as an e-commerce investment, opened “n11.com”, an open market platform that brings thousands of brands and stores.

{PRODUCTS WE USED}

Google Cloud Platform

The Challenge

Previously, N11.com was deploying on-prem Hadoop instances that were maintained by N11 team who faced complexity with growing dependencies and size. Moreover, the on-prem cluster was not scalable, costly by means of power, cooling, and facilities space. On business side, more complex and near real-time dashboards were required in order to track real-time purchases in order to take agile actions.

The Solution

On-prem Cassandra and Hadoop instances were migrated to BigQuery. Data pipelines were designed, developed, and scheduled to run daily ingestions of data. User events sourced from the web and mobile app are ingested in order to create near real-time analytics predictions. RFM segmentation application was created that segmentify customers using pre-defined categories and segments.

The Result

Our solution enables easy and secure data access for company employees, while supporting business growth through seamless and cost-effective scaling. With migration to BigQuery as part of our offering, the whole company enjoys resourceful insights at a high performance, where marketing teams analyzes yearly data and creates personalized campaigns.

TESTIMONIALS

“We need extracting timely insights from data on a day-to-day basis part of our business operations. Google Cloud perfectly suits our needs as it adaptively scales based on our all year long dynamic traffic loads and provides high performance and low latency for querying operations.”