This chapter covers:
- How a data project is usually structured
- How quality ties into design of a data project
- Quality when managing a data project
- Quality when collecting data
- Quality when processing data
- Quality when dissemintating data
- Quality when closing a data project
- Why you need to know about each stage when you identify needs
The first step to show you how to make data useful is to tell you how much I love a good murder mystery, especially the cozy kind ala Agatha Christie. Who doesn’t love Miss Marple and Hercule Poirot, the quirky amateur detectives? Those lovable detectives follow the trail left behind by the murderer, connect the dots, and finally reveal the dark and murderous side of a seemingly normal character.
Reading cozy murder mysteries is such fun: nothing is hidden from you while reading it. The clues are all there, they’re all hidden in plain sight. But you, as the reader, are unable to figure out how they relate or how important they are until the very last pages. The fun part of a cozy mystery is to have the same data as the quirky detective but not the same knowledge.
All cozy murder mysteries follow a similar structure. There are of course variations in the structure but these are the stages and their order in a cozy mystery: