In this workshop, you will learn to design a data pipeline solution that leverages Cosmos DB for both the scalable ingest of streaming data, and the globally distributed serving of both pre-scored data and machine learning models. The solution leverages Azure Cosmos DB in concert with the Azure Synapse Analytics through Azure Synapse Link to enable a modern data warehouse solution that can be used to create risk reduction solutions for scoring transactions for fraud in an offline, batch approach and in a near real-time, request/response approach. The Azure Cosmos DB change feed is used for near real-time scoring, while the Azure Cosmos DB analytical store is used for batch processing and high-performance analytical queries.

At the end of this workshop, you will be better able to design and implement solutions that leverage the strengths of Cosmos DB in support of advanced analytics solutions that require high throughput ingest, low latency serving and global scale in combination with scalable machine learning, big data and real-time processing capabilities.

Azure services and related products

• Azure Cosmos DB
• Azure Synapse Analytics
• Azure Data Lake Storage Gen2
• Azure Event Hubs
• Azure Kubernetes Service
• Azure Machine Learning Service
• Power BI

Speaker's Bio: Shivam Sharma, Co-founder TechScalable
Shivam is an author, cloud architect, speaker and Co-Founder at TechScalable. Being passionate about ever evolving technology he works on Azure, GCP, Machine Learning & Blockchain. He is also a Microsoft Certified Trainer. He architects’ solutions on Cloud as well on-premises using wide array of platforms/technologies.