Hello Everyone ,
I’m contacting you to ask for guidance on adding QuantifyAPI to our current system so that we may use it for customised reports. Right now, we’re pulling data for several metrics via the API, but we’ve run into a few problems that I hope someone here can help with.
Our main objective is to provide personalised reports that are suited to our particular requirements and incorporate information from various sources in our system.
We’ve successfully configured the bare minimum of API calls to retrieve data, but we’re having trouble with a few things:
Complex Data Aggregation: To produce an extensive report, we must merge data from multiple distinct endpoints. Is there a way to rapidly aggregate data from several API answers without sacrificing quality?
Filtering and Sorting: Prior to producing reports, we wish to apply unique filters and sorting standards to the data. What are the best ways to handle this inside the scope of QuantifyAPI?
Error Handling: In particular, rate constraints and unexpected data formats have caused us to run into some problems with error answers. I’d be grateful for any advice on strong error handling and maintaining data integrity.
Optimising Performance: We’re worried about how our API requests will affect performance as our data volume increases. When working with big datasets, are there any best practices or optimisation strategies that can improve performance?
https://quantifyapi.avontus.com/t/using-api-to-change-field-to-read-only-in-quantify-ui/servicenow
Any guidance, documentation, or examples that could assist us get past these obstacles would be greatly appreciated. Please let me know if you have any recommendations for specific tools or libraries to use when working with QuantifyAPI.
Thank you in advance.