This manual process is not only very time consuming, but is ripe for human error. Duplicate data also exists across all of these systems, and often in different formats. Finlabs automated the data gathering process as a routine that would run multiple times daily. Our automated process collects the data to one huge data pool, and cleans and re-processes it into a more suitable form for easy translation into billing and account information.
We built a process using Microsoft Azure Functions to automatically request data from a variety of data sources. The gathered data is then re-processed to ensure that it is usable and in the desired format to work within the system. To make this happen we utilized a combination of Azure Storage, Azure SQL Database, and Azure DevOps.
When utilizing data, precision is a must. Even more so when the data you are using must also be served up to customers for billing and reporting. Because we re-process the data our system ensures that the data is not only accurate but is presented clearly and is ultimately usable for Netox's end customers.
With an ongoing collaborative partnership established, we will be constantly working with Netox to further improve and evolve the platform to leverage more and more complex machine learning to create more
efficiencies and better accuracy.
Built on client's existing Microsoft Azure platform
Data processing to reformat into more usable formats
Hyperautomation to reduce the need for manual intervention
Vastly reduced errors in billing accuracy and reporting
Senior AI Engineer at Finlabs
This was a fascinating and challenging project in which I got to leverage my data engineering skills. It was very pleasing to see how much our solution actually helped Netox and the people handling finances and reports.
Working with Finlabs was a seamless experience. Their experts were able to quickly help us in streamlining our data collection and their contribution had a big impact on our business processes.
Tuulia Nissinen. Director, Customer Experience at Netox