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Woodgrove Bank, who provides payment processing services for commerce, is looking to design and implement a proof-of-concept (PoC) of an innovative fraud detection solution. They want to provide new services to their merchant customers, helping them save costs by applying machine learning and advanced analytics to detect fraudulent transactions. Their customers are around the world, and the right solutions for them would minimize any latencies experienced using their service by distributing as much of the solution as possible, as closely as possible, to the regions in which their customers use the service.
October 2020
- Application developer
- AI developer
- Data scientist
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.
Woodgrove Bank, who provides payment processing services for commerce, is looking to design and implement a PoC of an innovative fraud detection solution. They want to provide new services to their merchant customers, helping them save costs by applying machine learning and advanced analytics to detect fraudulent transactions. Their customers are around the world, and the right solutions for them would minimize any latencies experienced using their service by distributing as much of the solution as possible, as closely as possible, to the regions in which their customers use the service.
In this whiteboard design session, you will work in a group to design the data pipeline PoC that could support the needs of Woodgrove Bank.
At the end of this workshop, you will be better able to design 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.
Woodgrove Bank, who provides payment processing services for commerce, is looking to design and implement a PoC of an innovative fraud detection solution. They want to provide new services to their merchant customers, helping them save costs by applying machine learning and advanced analytics to detect fraudulent transactions. Their customers are around the world, and the right solutions for them would minimize any latencies experienced using their service by distributing as much of the solution as possible, as closely as possible, to the regions in which their customers use the service.
In this hands-on lab session, you will implement a PoC of the data pipeline that could support the needs of Woodgrove Bank.
At the end of this workshop, you will be better able to 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 Cosmos DB
- Azure Synapse Analytics
- Azure Data Lake Storage Gen2
- Azure Event Hubs
- Azure Kubernetes Service
- Azure Machine Learning
- Power BI
Globally Distributed Data
We welcome feedback and comments from Microsoft SMEs & learning partners who deliver MCWs.
Having trouble?
- First, verify you have followed all written lab instructions (including the Before the Hands-on lab document).
- Next, submit an issue with a detailed description of the problem.
- Do not submit pull requests. Our content authors will make all changes and submit pull requests for approval.
If you are planning to present a workshop, review and test the materials early! We recommend at least two weeks prior.