Explore big data architectures and Azure Machine Learning Studio integration in this comprehensive conference talk. Learn how to handle large datasets using Azure capabilities, connect to various data stores, and work with data loads, batches, and streams. Discover techniques for customizing machine learning processes with R modules, publishing endpoints for predictive analysis, and retraining models. Gain insights into scaling Azure ML web services to meet performance demands. Delve into topics such as Azure's big data capabilities, ML integration with different data stores, and designing architectures for large data volumes. By the end of this talk, acquire the knowledge to effectively use Azure ML for big data projects, adjust models using R modules, and scale solutions for optimal performance.