Things about analytics every newcomer should know
(Feel free to add your own)
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(Feel free to add your own)
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Raw data will almost always be messy and cleaning will be a big part of any project.
If you expect that, you'll be less frustrated with the amount of time you spend cleaning.
If you expect that, you'll be less frustrated with the amount of time you spend cleaning.
Relatedly: Data Engineers are important and if you don't have one, you'll probably wish you did.
Statistical significance is arbitrary & can be abused.
Many organizations (in and out of sports) still have very limited or no analytics infrastructure.
There's a *lot* of low-hanging fruit.
There's a *lot* of low-hanging fruit.
The term "AI" is overused.
Statistics is not purely objective.
Humans decide what goes into models & how those models are built.
Humans decide what goes into models & how those models are built.
The process of communicating quantitative insights is as important as the process of generating those insights.
Visualizations should as as simple as possible while still conveying the underlying information.
Constantly looking things up on Stack Overflow is not only OK, it's an essential part of programming.
Quantitative analysis is often most effective when *combined* with qualitative analysis.
Each genre of analysis can keep the other's gaps & biases in check.
Each genre of analysis can keep the other's gaps & biases in check.
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