Share with:
One of the business teams at client’s end was overwhelmed with manually tracking 800–900 alerts per month. With high volumes of data and manual dependency for investigation tracking, errors and inefficiencies crept into reporting processes. Scalence stepped in to automate the data flow using a custom-built solution, transforming how alerts were handled, logged, and analyzed.
The business team was relying on repetitive manual steps to copy and log alerts and associated details from multiple dashboards. This error-prone process involved switching between tabs, handling multiple data points for each alert, and feeding them into a shared tracking sheet—slowing down investigations and impacting data reliability. The process lacked consistency, repeatability, and scalability.
Scalence designed and deployed a lightweight automation framework using SQL and Python scripting. A SQL script was developed to extract all triggered alerts daily. Then, using Python, the alerts were automatically written into a centralized tracking sheet, reducing human involvement and eliminating copy-paste dependency.
This end-to-end automation removed redundant effort, standardized the data format, and ensured that the client’s internal Issue Tracker system tickets and other investigation details were accurately captured with minimal manual input. The new system allowed for rapid review of alert status by Billing ID and simplified cross-team collaboration.
The automation led to a significant increase in data accuracy and productivity, freeing the team from mundane tasks and allowing more time for in-depth analysis. It also established a repeatable, scalable process for future integration with other systems and tools.
Scalence Navi