The customer approached Cloudreach for support and assistance setting up a Cloud Landing Zone to utilize GCP’s PaaS Services. The primary objective was to migrate a key application to operate in GCP, to enable the business to derive new revenue from customers looking to access various samples of their data that could feed into their own models.
They also asked for a feature to enable external data scientists to quickly access samples of data, allowing them to evaluate the feed. We worked with a DevOps approach, in collaboration with the customer’s team.
After a successful demonstration of GCP’s functionality, we helped the customer build their product on GCP. The product makes use of Serverless & PaaS technologies to enable consumers to download Jupyter notebooks that have been pre-configured to access sample data feeds.
Following a successful proof of value, we built for the customer a data platform that enables their end-customers to access, query and analyze their extensive archive of pricing and tracing data using GCP. Along with improving the speed of access to this data, it enables them to quickly and easily ingest their data into their own models.
The underlying platform is built around Google BigQuery and Google Cloud Functions.
Through leveraging GCP, end-customers of our client are now able to access large datasets in a fraction of the time that they would typically experience, as well as benefiting from a reduction in cost from the storage of that data.
The platform also allows the customer to monitor the usage and consumption of data, allowing them to better understand the value of their feeds and how to subsequently monetize the data to relevant customers.
About the Customer
This global financial company provides a broad range of finance and risk services to thousands of institutions in almost 200 countries.