Describe common architectures for processing big data using Azure tools and services.
Describe how to use Azure Stream Analytics to design and implement stream processing over large-scale data.
Describe how to include custom functions and incorporate machine learning activities into an Azure Stream Analytics job.
Describe how to use Azure Data Lake Store as a large-scale repository of data files.
Describe how to use Azure Data Lake Analytics to examine and process data held in Azure Data Lake Store.
Describe how to create and deploy custom functions and operations, integrate with Python and R, and protect and optimize jobs.
Describe how to use Azure SQL Data Warehouse to create a repository that can support large-scale analytical processing over data at rest.
Describe how to use Azure SQL Data Warehouse to perform analytical processing, how to maintain performance, and how to protect the data.
Describe how to use Azure Data Factory to import, transform, and transfer data between repositories and services.