Background #

An internationally acclaimed Economist developed an international trade application for local and international clients. The initial application was shipped as a Qlik (Tableau) package. The prohibitive licencing costs, significant effort to update as well as the extremely large datasets made this distribution model difficult. The application was ported to a web application.

Solution provided #

A specialised web application was developed using the Vuejs framework for the front-end development and Django as the backed. The solution is connected to a managed Postgres database and hosted via a load balancer.

Unique project attributes #

The Django backend primary deals with complex report generation based on a specific set of parameters and study boundaries defined by the user using the front end application. The application needed these outputs to be in the main Microsoft Office formats due to client requirements.

Specialised Word report generation #

One of the main strengths of the application is the automatic generation of Microsoft Word reports. PDF reports would not be sufficient since it is mostly non editable. The clients would obtain a near 100% populated Word report for the specific study that was conducted and only has to do minimal editing for specific use cases. A template system was developed that allows for the population of a present Word template as well as writing Pandas Data frames directly into embedded Word graphs. Each word document will have the client template and corporate identity applied to the document. This includes

dynamic image insertion
table creation and population
live and linked graphs
dynamic addition of reporting sections based on number of report entities
dynamic interpretation of results leads to specific text updates in the report

Specialised PowerPoint generation #

The application also generates publication ready PowerPoint slides with the client template and corporate identity applied to the slide deck.

Specialised Excel generation #

The application also allows for the offloading of large datasets into a pre-set Excel analysis environment. This enables more advanced users to fine tune a specific economic study.

Timeframe and Budget #

The project was developed over a period of two years with a Budget of R1,500,000. The appication is stull under development and more features are introduced during a 6 week cycle.

Tools Employed #

Frontend #

vuejs
vuex
vue-router
axios

Backend #

Python
Django
pandas
postgres

Deployment platform #

Digital Ocean