Summary of the Preste Project

As the contract concludes, Friday, August 13th, 2021

Agreement and Completion Time

The last update of the agreement with Preste, which can be considered as the start of the contract, took place on June 8th, 2021. The delivery of the finished product is for September 1st, 2021. The project was, therefore, carried out over a period of three months. The main analyst assigned to the project was William César Lareau, under the supervision and guidance of senior analyst Simon L’Abbé St-Vincent.


Create a demographic portrait of Québec of Preste artists. The analysis results were presented in the form of a dashboard.


The data used are from an aggregation web service: . Under our supervision, Preste recruited this service and was able to extract quality data on the web presence of their artists (Incubators: Spotify, Instagram, Wikipedia, YouTube, local radio stations, Shazam etc.) (Variables: Fanbase index, engagement index, global index, popularity index, number of views, number of followers, and several monthly variations of these same variables). This data is accessible, but must be exported to the website before placing it in the appropriate location in the project file.


This was all done using the Power BI application from the Office 365 Suite, with the exception of a technical difficulty that was solved using Python’s data analysis library, Pandas. The Office suite offers a data query tool compatible with Excel and Power BI: Power Query. This tool was particularly useful for creating data tables that compose the Power BI template (which is the dashboard).


The dashboard enumerates several pages in three parts:
1. A narrative presenting the profile of the artists according to several aspects of their cultural presence: fanbase, popularity, commitment, reach, concert history, …
2. A geographical perspective of the different musical genres in order of preference in the different municipalities of Québec.
3. A simple music monitoring system.

Final Observations

The project has further potential. An automated connection to Chartmetric is a possibility that would direct data needing extraction straight to the Power BI solutions folder. Moreover, the data model would benefit further from being solidified to ensure the functionality of the dashboard long-term. Finally, to improve their concert database, Preste could conduct an internal follow-up which would, in turn, benefit the quality of the entire analysis.

William César Lareau


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