Peter Faasse

Talent Data Labs is an HR analytics and automation company. Peter is responsible for data management for a major client based in Sweden called Nova Talent, which handled in Business Intelligence concerning talent in the Nordics (Sweden, Norway, Denmark, and Finland) and Spain.

Working on HR-matching and data storage project:

• Ensured the continuous matching and storage of company and talent data.
• Collected data through surveys and web scraping, cleaning and matching this data using python, and storing this data in google sheets.

Working on database and visualization project:

• Designed and created a new database in MySQL and AWS server to which all the existing data is being transported.
• Adjusted existing scripts to run daily updates on this data based on new data becoming available through surveys.
• Created several Tableau dashboards which could be used by the team at Nova to easily create client specific dashboards, to present insights in their matches.

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.

Afstudeerbegeleider.nl is a company that helps students with their thesis and in the field of data analysis, SPSS, and statistics to perform quantitative research for companies and organizations.

• Provided SPSS and statistics tutoring for clients.
• Trained and provided support for new consultants.
• Designed and performed quantitative studies for companies and organizations.