Using AWS QuickSight to Improve your Business
AllCode helped IBids.io integrate their application with AWS’ QuickSight suite to better improve its functionality with the use of data-driven customer analytics. Our engineers applied their knowledge in conjunction with their understanding of RDS to thread data through to a dashboard for a client.
IBids enables people in the Dominican Republic to acquire information on the bids for state sales opportunities. IBids reached out to AllCode because they needed engineering resources to meet with members of the AWS QuickSight team in Seattle, Washington.
Ibids.io’s application proposed a project that had been accepted into the AWS Embedded Analytics Data Lab to help with QuickSight integration. The main issue was figuring out a method of properly embedding that data source into the aforementioned dashboards. With that, they requested two of our experts to join the development team for a 4-week phase of Pre-Lab work with a subsequent week of dedicated build-time. The idea was for the experts to replicate existing templates and work for five hours per week over the 4-week phase and an additional forty hours during the execution phase.
How AllCode helped IBids.io
Over the span of a week, AllCode engineers were invited to a datalab to QuickSight dashboards for this use case. Those dashboards were then embedded into the REACT application. This way, our engineers had a better grasp of the use cases for QuickSight and the APIs we would be working with. The project required multiple iterations of the framework before it successfully worked. The solution was a two-pronged approach.
One of the options was to embed anonymously to allow open access to provide the same data to whoever has access. This is helpful in situations where the data is readily accessible, making it unnecessary to log the user on QuickSight.
Comparatively, user-based embedding is for circumstances where the information being accessed is much more personal. Obviously, some dashboards will call for information to be kept separately on a per-user basis or users will be only interested in more specific bits of information.