AWS, Cloud Computing

3 Mins Read

Manage and Analyze Financial Data using Amazon FinSpace

Introduction to Amazon FinSpace

Amazon FinSpace is an analytics and data management service purpose-built for the financial services industry (FSI). It is used to store, catalog, prepare and analyze financial industry data It reduces the time we spend finding and preparing petabytes of data to be ready for analysis from months to minutes. Financial services organizations analyze data from internal data stores like actuarial, portfolio, and risk management systems and also petabytes of data from third-party data feeds, such as historical securities prices from stock exchanges. It will take months to find the right data, get permission to access the data in a compliant way, and prepare it for analysis. With FinSpace, we can overcome these issues.

FinSpace eliminates the heavy lifting of building and maintaining a data management system for financial analytics. With the help of it, we collect data and catalog it by relevant business concepts such as asset class, geographic region, or risk classification. It makes it easy to discover and share data across our organization by compliance requirements. We define our data access policies in one place and FinSpace enforces them while keeping audit logs to allow for compliance and activity reporting. It also includes a library of 100+ functions, like Bollinger bands and time bars, to prepare data for analysis.

Why Amazon FinSpace?

It simplifies the process of discovering data, gaining permission to access data, and transforming data to be ready for analysis, therefore saving months of prep work done by financial services customers today.

Financial services organizations depend on hundreds of datasets sourced internally or externally to build investment models, manage risk, and improve customer experience. It is taking analysts longer and longer to test new research ideas as data volumes are increasing, customers want to use more diverse datasets, and compute resources cannot keep up with the data volumes and latest algorithms. FinSpace helps analysts be more agile and productive by reducing the time they spend searching for data, obtaining access to the data, and acquiring the compute resources needed to match their data volumes.

Customized Cloud Solutions to Drive your Business Success

  • Cloud Migration
  • Devops
  • AIML & IoT
Know More

How Amazon FinSpace works?

Workflow

Source – AWS

Benefits of Amazon FinSpace

  1. Import data easily: The SDKs allow us to load data files into it in bulk, ad-hoc fashion, or daily. Connect daily historical data feeds from stock exchanges and data providers into FinSpace.
  2. Store and catalog data with business terms: Create a business data catalog with business taxonomy to organize data so that business users can easily discover it. Organize data by asset classes, data types, regions, or industry.
  3. Track versions of data: Create bi-temporal views that analyze data the way it looked at a particular date and time. Reproduce historical financial models for compliance and audit purposes.
  4. Prepare and analyze data at scale: Use FinSpace notebook along with integrated managed Spark clusters to run analysis on petabytes of data. With FinSpace, Scale computes with spark clusters on an as-needed basis.
  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 Athena, Redshift, EMR, QuickSight, and SageMaker.
  6. Financial time series analysis: Execute financial time series analysis on high-density market data using an integrated time series library with over 100 embedded functions including technical indicators and statistics such as Bollinger Bands.

Steps to use FinSpace

  1. Launch FinSpace from Amazon Web Services (AWS) console and configure how data will be organized in the catalog for easy searching.
  2. Add the data which will be needed for analytics.
  3. Describe and organize the data so that the data can be searched from the catalog.
  4. Prepare the data by creating current data or historical views partitioned to optimize performance.
  5. Analyze the data with integrated Jupyter notebooks and managed Spark clusters for data processing at scale.

Conclusion

Amazon FinSpace is a game changer for most of Financial Services organizations. It radically reduces the time it takes for Financial Services organizations’ customers to do analytics across petabytes of data, making it significantly easier for them to identify new sources of revenue, attract customers, and reduce risk and cost.

Get your new hires billable within 1-60 days. Experience our Capability Development Framework today.

  • Cloud Training
  • Customized Training
  • Experiential Learning
Read More

About CloudThat

CloudThat is also the official AWS (Amazon Web Services) Advanced Consulting Partner and Training partner and Microsoft gold partner, helping people develop knowledge of the cloud and help their businesses aim for higher goals using best in industry cloud computing practices and expertise. We are on a mission to build a robust cloud computing ecosystem by disseminating knowledge on technological intricacies within the cloud space. Our blogs, webinars, case studies, and white papers enable all the stakeholders in the cloud computing sphere.

Drop a query if you have any questions regarding Amazon FinSpace and I will get back to you quickly.

To get started, go through our Consultancy page and Managed Services Package that is CloudThat’s offerings.

FAQs

1. Is Streaming data supported in FinSpace?

ANS: – Yes, collect streaming data into change sets, which then can be loaded into FinSpace using the FinSpace API.

2. Is FinSpace available in all regions?

ANS: – No, it is available only in Europe (Ireland), Canada (Central), US East (N. Virginia, Ohio), US West (Oregon) for now.

3. Can I track activity in FinSpace for Audit and Compliance purposes?

ANS: – Yes, you can generate and export reports using FinSpace Audit Report functionality.

WRITTEN BY Suresh Kumar Reddy

Yerraballi Suresh Kumar Reddy is working as a Research Associate - Data and AI/ML at CloudThat. He is a self-motivated and hard-working Cloud Data Science aspirant who is adept at using analytical tools for analyzing and extracting meaningful insights from data.

Share

Comments

    Click to Comment

Get The Most Out Of Us

Our support doesn't end here. We have monthly newsletters, study guides, practice questions, and more to assist you in upgrading your cloud career. Subscribe to get them all!