Once you and your team start to build the project, you may realize that it requires effective management strategies. Can you use traditional software development methodologies for data science projects? What caveats do you have to look for? What processes should you use to manage development iterations? How can you sustain a balance between research and implementation? How should you deal with situations of extreme uncertainty?
This section contains the following chapters:
- Chapter 7, Managing Innovation
- Chapter 8, Managing Data Science Projects
- Chapter 9, Common Pitfalls of Data Science Projects
- Chapter 10, Creating Products and Improving Reusability
