What makes data analysts good- Cassie Kozyrkov

Data analysts look for facts and provide inspiration , At the same time, try to waste your time as little as possible in this process （ And your time ！）. In order to get the best inspiration return , They have to master many different forms of speed , Include ：

• The speed at which promising and relevant data can be obtained .（ Domain knowledge .）
• The speed at which data is ready for operation .（ Software skills .）
• Speed of summarizing data .（ Math skills .）
• The speed at which data is abstracted into their own brains .（ Data visualization skills .）
• The speed at which data summaries are entered into the stakeholders' brains .（ Communication skills .）
• The speed at which decision makers are inspired .（ Business savvy .）

Beautifully visualized and effectively communicated trivia is a waste of your time ; The exciting findings are misunderstood as a waste of your time ; Careful attempts at garbage data sources are a waste of your time ; Irrelevant anecdotes are a waste of your time ; Anything the analyst brings you that you don't think is worth your time …… It's a waste of your time .

 

Analysis game is about optimizing inspiration every minute .

Don't be confused by the simple explanation of speed . A sloppy analyst is constantly addicted to shiny nonsense “ insight ”, It will only slow everyone down in the long run .

 

Evaluate Analyst performance

For those who like performance appraisal , Please note that , You can't use inspiration per minute to measure your analyst .

This is because the maximum amount of inspiration that can be extracted （ Subjectively defined by the decision-maker ） Varies by dataset . But you can assess their skills by letting them relax on benchmark datasets that you are already familiar with （ Not job performance ）.

For example , If you ask two analysts to draw inspiration from a foreign language textbook , So much better （ faster ） The analyst may be a native speaker of the language . You can assess their relative skills by measuring how quickly they understand the paragraphs you write in that language .

 

Byteboard Is an innovative technology interview start-up company , they Recently launched A data analysis skills assessment . It uses real scenes and beautiful interfaces to measure data exploration 、 Data Extraction 、 Quantitative communication and Business analysis Ability to wait for tasks . Of course , They intend to use it as a way to help you interview new candidates , But there's no reason why you can't also use it to quickly test your current analysts .

 

Skills do not guarantee influence . It depends on your data .

If you point both analysts to a mysterious textbook that you have never opened , You can't hold them accountable for every minute of inspiration they find , Because this book may be full of garbage . If so —— No matter how fluent they are ！—— No one will find any inspiration for you …… It's not their fault . Having a textbook doesn't mean you will learn something useful . The same is true for datasets ; Their quality and relevance are equally important .

Textbooks are a good analogy for data sets , So there are a few things to keep in mind about data sets and Textbooks ：

• One decision-maker's garbage may be another decision-maker's treasure . Just like textbooks , Datasets are only useful for you if they cover the topics you want to know .
• If it had a human author , It's subjective . Just like textbooks , Data sets also have human authors , Its bias will affect the content .