Technical Inspiration
Curious to see what you can build after following this course? Or looking for some ideas how to structure the directory structure of your team project?
Here, we provide some inspiration, based on the creative and/or reproducible work of others!
Contribute to this section
If you find a good example, add it via a pull request, please! Curious how? Follow our GitHub tutorial.
End-to-end workflows
Research projects
- Categorization of Spotify playlists using machine learning
- Hiding of Instagram Likes
- Sales-based brand equity ( Paper, Code)
Documenting data
- Playlist Promotions and New Releases at Spotify
- Spotify Releases (2015-2018)
- The playlist ecosystem at Spotify
Templates
Automation templates
- Simple setup with R, Make and Latex
- Tutorial for starting up a new empirical research project
- SnakeMake - an alternative to
make
Analysis templates
Deployment templates
- ShinyApps & Covid-19
- ShinyApps & advertising effects
- https://pudding.cool/ - visual essays and digital culture
Packages
Readings
Error handling & starting to code
When you start programming, Google will be your best friend! Next to just searching on Google, there are several websites on which programmers help each other out.
Reproducible science
- Engineering Practices for Data Scientists
- Social Science Editors: Data and code replication packages
- Data and Code Policy of the American Economic Association
- The Turing Way
Also check out the cheat sheets for relevant information to use in your team project (e.g., rendering.rmd
files inmake
, using Shiny apps, Git commands and more!)
Learn SQL
SQL is one of the most prominent ways to extract data from databases - either from research databases, or from companies’ internal databases. As a marketing analyst, it is crucial to learn how to extract data from existing databases. This can be very challenging, because data is not readily prepared (but needs to first be prepared to be extracted). This is made even more complicated because the databases of firms do not consist of a thousand rows, but may include millions or even billions of rows.
In short, learning the SQL language significantly improves your chances to score a good job in the job market. This is an optional tutorial which walks you through the main ideas of SQL. In going through it, try to see similarities and differences with regards to other things that you learn in Data Preparation and Workflow Management.