Qubole brings machine learning to the data warehouse
Enabling Machine Learning on the Data Warehouse with Apache Spark on Qubole
Data Wrangling and Predictive Analytics for the 2019 Cricket World Cup Using PySpark & Python
How to acquire, transform and analyze semi-structured data and apply predictive analytics to predict future performance
How Data Science Teams Can Succeed at Machine Learning at Enterprise Scale
Strategies to address common challenges data science teams face as they scale up ML operations
Using Qubole Notebooks to Predict Future Sales with PySpark
Build and use a time-series analysis model to forecast future sales from historical sales data
AgilOne: Machine Learning at Enterprise Scale
AgilOne runs a variety of workloads for querying data, running ML models, orchestrating ML workflows, and more on Qubole
Leveraging Streaming and Batch Data Sets for ML Applications
Learn how to use Qubole to acquire and transform data sets for data science and analytics, make data sets available to different users, and fully leverage your data lake.
TrafficGuard Halts Digital Ad Fraud with Qubole
TrafficGuard relies on big data processing to detect and prevent ad fraud, which requires a robust infrastructure.
Return Path Accelerates Data Science Projects, Saves Thousands in Compute Costs with Qubole
Return Path drove down compute costs and was able to deliver self-service access to data with Qubole
Spotad: Rebuilding and Optimizing Real-Time Mobile Adverting Bidding with Qubole
Migrating to Qubole saved Spotad more than 50 percent in its operating costs almost instantly.