Introduction

Data Preparation and Workflow Management (dPrep)

Instructor: dr. Hannes Datta Follow @hannesdatta

Course codes: 328059-M3 (fall, block 1) and 328062-M3 (spring, block 3)

This edition: August - October 2022 | Next edition: February - April 2023

Engineer data sets and manage research projects efficiently

Welcome to the course website of dPrep, where you learn how to efficiently manage empirical (marketing) research projects.

The course offers seats to Research Master and PhD students from outside of Tilburg University.

Check out the course syllabus & learning objectives View the schedule Enroll now!

Why should you take this course?

Many students and researchers perceive the process of doing research as rather simplistic: a bit of data cleaning here and analysis there, and you’re done. While this mostly isn’t a problem when working on small-scale projects, this approach won’t work anymore once you work on your empirical theses (e.g., for Marketing Analytics), or join an analytics-focused company.

Therefore, in this course, you will professionalize your way-of-working. In particular, we’ll zoom in on complex, reproducible data preparation workflows (think of structured and unstructured raw data, derived from multiple sources, provided in multiple delivery batches, with lots of missing data, etc.).

Throughout the course, you’ll be using workflow principles of reproducible science that are documented at Tilburg Science Hub. This open source platform will likely become your go-to page for analytics and workflow related issues for years to come.

This website

This website is the backbone of the course, and features the following main sections.

  • The course section features the syllabus, schedule, and grading details.

  • The weekly modules consist of live streams, readings, and prerecorded clips. Even if you’re not enrolled in this course, you can watch these clips, but interaction with the course instructor is reserved for enrolled students only.

  • The tutorial section offers self-guided tutorials that teach the principles of data preparation and workflow management.

  • Finally, this course uses building blocks and examples to provide solutions and inspiration for your project work.