Posted On: Nov 17, 2022
Amazon FinSpace is an analytic data hub for capital markets customers that enables analysts and data engineers to access data from multiple sources and transform it using Amazon FinSpace’s managed Apache Spark Engine with Capital Markets Time Series Analytics Library. Starting today, datasets developed in FinSpace can also be used by AWS Analytics and Machine Learning services, such as Amazon Redshift, Amazon Athena, Amazon QuickSight, Amazon EMR, and Amazon SageMaker. This allows customers to integrate data from FinSpace into their analytics and ML workflows.
Access is enabled using Amazon FinSpace’s new data view sharing capability. Amazon FinSpace data views provide access to query the data stored in Amazon FinSpace. Once a customer enables data view sharing, all data views are available as tables in a customer's Lake Formation data lake as a Lake Formation table share. Then, Lake Formation data lake administrators can grant permissions to data lake users, which can access the shared data in the data lake through AWS analytics services such as Amazon Redshift, Amazon Athena, Amazon QuickSight, Amazon EMR, and Amazon SageMaker.
In an example scenario, a risk analyst using FinSpace could perform Value at Risk (VaR) calculations on a portfolio using the Apache Spark Engine with Capital Markets Time Series Analytics Library. The output of this process would be a set of risk scores for the portfolio that could then be shared using data view sharing. Then, the customer could run an automated Athena query to combine it with other risk data and display it in a consolidated risk dashboard in QuickSight.