What is Amazon FinSpace? - Amazon FinSpace

What is Amazon FinSpace?


Amazon FinSpace Dataset Browser will be discontinued on November 29, 2024. Starting November 29, 2023, FinSpace will no longer accept the creation of new Dataset Browser environments. Customers using Amazon FinSpace with Managed Kdb Insights will not be affected. For more information, review the FAQ or contact AWS Support to assist with your transition.

Amazon FinSpace is a fully managed data management and analytics service that makes it easy to store, catalog, and prepare financial industry data at scale.

FinSpace removes the heavy lifting of building and maintaining a data management system for financial analytics. FinSpace provides a Managed kdb Insights analytics engine powered by the industry recognized kdb analytics engine. It also features the Dataset browser that you can use to collect data and catalog it by relevant business concepts such as asset class, risk classification, or geographic region; which makes it easy to discover and share across your organization.

To see all the regions FinSpace is available in, visit the AWS Region page.

Managing data in financial services

Financial services customers store petabytes of data which is collected from both internal and external data sources. The data is generated from their internal applications such as portfolio management systems, actuarial applications, order and risk management systems, and external data such as stock exchanges and financial data providers. The data is typically used for use cases including but not limited to quantitative research, product pricing, customer experience, and investment management. The size of the data is growing and the number of sources that FSIs are receiving data from is also increasing which makes it hard to manage and track. FSI customers want to make this data available in a self-service and secure way to their analysts and data scientists for analysis. The analysts want to discover the data easily, and analyze it at scale.

Benefits of Amazon FinSpace with Managed kdb Insights

With Managed kdb, you can:
  • Eliminate operational overhead with Managed kdb Insights for high performance capital markets analytics.

  • Manage spend, keep up with market volatility, and ensure high-availability with auto scaling and multi-Availability Zone for kdb applications.

  • Launch new analytics infrastructure on demand and accelerate migration of on-premise kdb systems to AWS.

Benefits of Amazon FinSpace Dataset browser

With Amazon FinSpace Dataset browser, you can:

  1. Import data easily – The SDKs allows you to load data files into FinSpace in bulk, daily, or ad-hoc fashion. Connect your daily historical data feeds from stock exchanges and data providers into FinSpace. For more information, see Loading and analyzing data.

  2. Store and catalog data with business terms – Create a business data catalog with your business taxonomy to organize data so that your business users can easily discover it. Organize data by asset classes, regions, data types, or industry. For more information, see Configuring a business data catalog.

  3. Track versions of data – Create bi-temporal views that let you analyze data the way it looked at a particular date and time. Reproduce historical financial models for audit and compliance purposes.

  4. Prepare and analyze data at scale – Use FinSpace notebook with integrated managed Spark clusters to run analysis on petabytes of data. Scale compute with spark clusters on an as-needed basis. For more information, see Prepare and analyze data.

  5. Share data managed in FinSpace – Share data view tables with a Lake Formation data lake so that the data can be easily queried with AWS analytics engines like Amazon Redshift, Athena, Amazon QuickSight,Amazon EMR, and SageMaker. For more information, see Data views sharing.

  6. Financial time series analysis – Run financial time series analysis on high density market data using integrated time series library with over 100 embedded functions including statistical and technical indicators such as Bollinger Bands. For more information, see Time series library.