Good business decisions cannot be made with bad data. At Uber, we use aggregated and anonymized data to guide decision-making, ranging from financial planning to letting drivers know the best location for ride requests at a given time.
But how …
Ritesh Agrawal
Ritesh Agrawal is a senior data scientist on Uber's Data Science team, leading the intelligent infrastructure and developer platform teams. His work is focused on finding innovative ways to use data science and AI to make Uber’s infrastructure more adaptive and scalable and enhance developer productivity.
Engineering Blog Articles
Less is More: Engineering Data Warehouse Efficiency with Minimalist Design
Maintaining Uber’s large-scale data warehouse comes with an operational cost in terms of ETL functions and storage. In our experience, optimizing for operational efficiency requires answering one key question: for which tables does the maintenance cost supersede utility? Once identified, …
Solving Big Data Challenges with Data Science at Uber
The data involved in serving millions of rides and food deliveries on Uber’s platform doesn’t just facilitate transactions, it also helps teams at Uber continually analyze and improve our services. When we launch new services, we can quickly measure success, …
