Case Studies

📄️ 99 Group

References

📄️ Airbnb

📄️ Booking.com

📄️ Jeevansathi

The data is mainly collected via three sources, i.e., RDBMS, MongoDB, and through websites and apps. This data is loaded into the data lake in batches or in real-time with the help of various tools like Maxwell-Daemon, Apache Sqoop, MongoExport, Change Stream, etc.

📄️ Myntra

1. Janus : Data processing framework at Myntra

📄️ Uber

Uber's Big Data Platform: 100+ Petabytes with Minute Latency

Other Resources

1. The Big Book of Data Engineering with Databricks
2. How we store and process millions of orders daily at Grab
3. Data Engineering at Uber
4. How the Netlify Data Team Migrated from Databricks to Snowflake
5. Data Engineering at Upwork
6. Building a Modern Data Stack at Whatnot
7. Tuning Whatnot’s Data Platform for Speed and Scale
8. Coupang Eats Data Platform
9. Uber Freight Carrier Metrics with Near-Real-Time Analytics
10. Towards Machine Learning Observability at Etsy
11. Modernizing the Data Engineering Stack in 99 Group
12. Cookbook of Case Studies
13. Upgrading Data Warehouse Infrastructure at Airbnb
14. Monitoring machine learning systems at Faire