Part I. Introduction: 1. Motivation; 2. Gearing up; 3. Data = content + structure; Part II. Data in Files: 4. Storing data in files; 5. Managing data in spreadsheets; 6. Basic data management in R; 7. R and the tidyverse; Part III. Data in Databases: 8. Introduction to relational databases; 9. Relational databases and multiple tables; 10. Database fine-tuning; Part IV. Special Types of Data: 11. Spatial data; 12. Text data; 13. Network data; Part V. Conclusion: 14. Best practices in data management.