WESP creates and sells Business Intelligence (BI) for the automotive branch and is focused on aftersales.
Working on a web scraper project:
- Built and collected pricing data from several car parts retailers.
- Created a web scraper using Python to collect available data from several websites and store all this data in a MySQL database.
- Connected the collected data to the existing database owned by WESP and to other applications.
Working on the impact project (WESP is now actively using this study; also published this in Aftersales Magazine):
- Conducted a study into the impact of using Business Intelligence (BI) on performance for organizations in aftersales.
- Took a large sample of clients from WESP and analyzed the change in performance before and after usage of BI by WESP on 15 different performance indicators.
- Utilized multilevel linear regression analyses to see what the impact of BI-usage was on performance.
Working on predictive forecasting of labor costs project:
- Applied multilevel linear regression models to predict labor costs.
- Developed research design, data preparation, and data analyses.
Working on a categorization project:
- Managed data preparation.
- Created and tested different machine learning algorithms.
- Ran and adjusted different categorization models.
- Presented preliminary results.
