alert! The pitfalls of data analysis?

In our last article, we sorted out some moments of glory and pride in data analysis, including the importance of data analysis, the value of data analysis output, and a summary of classic data analysis cases. I believe that everyone has a corresponding, three-dimensional and comprehensive understanding of the value and importance of "data analysis" and their own insights. (For details, please see: The Glory and Pride of Data Analysis) However, in our daily work, you must have heard words such as "speak with data", "use data to tell stories" and so on. It can be seen that data is increasingly valued by each of our enterprises or business line personnel, and has become the most important reference and decision support for our practical work.

But at this time, many data analysts tend to mobile number list pay too much attention to data or analysis methodology, especially for those who are just getting started. In the process of interpreting data, they are affected by data sources, collection methods, statistical caliber, analysis methods, business experience, thinking Influenced by factors such as methods, there will be some "traps" that are easy to ignore, so that the results are likely to be biased. Therefore, it is good to pay attention to data analysis, but you must not fall into the "trap" of data analysis.

Then, in this article, we will discuss and sort out several possible common "traps" in the process of data analysis from the perspective of the business level. The purpose is to provide some useful experience sharing for those who are just getting started, products, operations, etc. When encountering these situations in the work scene, you can try to avoid some "traps" that you don't pay much attention to.