【文件属性】：
文件名称：bad data handbook
文件大小：10.72MB
文件格式：PDF
更新时间：2022-01-28 11:13:16
bad data 坏数据
It’s tough to nail down a precise definition of “Bad Data.” Some people consider it a
purely hands-on, technical phenomenon: missing values, malformed records, and cranky
file formats. Sure, that’s part of the picture, but Bad Data is so much more. It includes
data that eats up your time, causes you to stay late at the office, drives you to tear out
your hair in frustration. It’s data that you can’t access, data that you had and then lost,
data that’s not the same today as it was yesterday…
In short, Bad Data is data that gets in the way. There are so many ways to get there, from
cranky storage, to poor representation, to misguided policy. If you stick with this data
science bit long enough, you’ll certainly encounter your fair share.
To that end, we decided to compile Bad Data Handbook, a rogues gallery of data troublemakers.
We found 19 people from all reaches of the data arena to talk about how data
issues have bitten them, and how they’ve healed.