The data used comes from an aggregation web service: chartmetric.com . Under the supervision of Synapse C, Preste became a member of this service and quality data on the web presence of their artists could be extracted (incubators: Spotify, Instagram, Wikipedia, Youtube, local radio stations, Shazam, etc.).
This data is accessible, but needs to be exported to the website mitten, to then be routed to the right place in the project folder.
(Variables: fanbase index, engagement index, global index, popularity index, number of reads, number of subscriptions, and several monthly variations of these same variables).
All this was done using the Power BI application from the Office 365 suite and the Pandas library from Python. The Office suite offers a data query tool compatible with Excel and Power BI: Power Query. This tool was particularly useful to create the data tables that form the model of the Power BI solution, the dashboard.
The dashboard counts several highlights 3 parts:
1. A storytelling that profiles artists according to several aspects of their presence in the cultural landscape: fanbase, popularity, engagement, reach, concert history, among others.
2. A geographical view of the different musical genres in preference in the different municipalities of Quebec.
3. A simple music watch.
An automated connection to Chartmetric could be possible and would route the data to be extracted directly to the Power BI solution file. The data model could be solidified and a follow-up could be done internally at Preste to improve their own concert database; this data would then benefit the quality of the analysis.
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