We are currently developing an integrated, automated KPI tracker. The goal of the project is to optimise the internal KPIs of our organisation through the use of modern day tools and techniques. The end-to-end process includes an application for data collection, secure online data storage, automation of the calculation process, and an interactive dashboard to display the KPI metrics.
What we have done:
We created an online application for consultants to track their time and update their project statuses. The data is then automatically uploaded to an online database where it is stored. Other data, e.g. data related to the day-to-day business operations, is also uploaded and stored in the secure online data storage unit. The data is then interpreted and visually represented through a custom dashboard which allows relevant stakeholders to view real-time data as needed.
The project involved:
Data collection through online application
Data gathering from specific sources related to the day-to-day business operations
Creation of a Lambda function to trigger the data collection and storage of data in an AWS S3 bucket
Utilising Python to create a program to:
Automatically import and collate the data from the database in various formats such as CSVs, spreadsheets, static reports, etc.
Process the data and determine basic KPI metrics
Build an interactive dashboard, to display the KPI metrics
Creating a Docker image of the code that is hosted through EC2 on AWS
Deployment of the repository on ECS so the dashboard could be accessible via an IPv4 (http) address.