1, clear their analysis of the theme

such as you have a different part of the sale of data, then at the moment you want to do a thing, it becomes particularly important, you want to analyze part of the results of the situation, or you want to see which customer is a high-quality customers? At this point we need to be clear about the subject of profiling.

2, reasonable data modeling

After the clear theme, we have to transaction modeling, transaction modeling followed by confirmation of technical modeling.

Then to confirm what the norms of quality customers, such as income issues, have contact information, more than 100,000 sales and purchases. Then we only need to collect these owned information fields for this modeling. Proper data modeling can take the burden off of profiling.

?3, remove dirty data

Dirty data can be interpreted as abnormal data, such as telephone numbers in the presence of Chinese characters, gender in the presence of other characters. Then this part we need to clean, strict requirements.

On how to control the quality of data analysis, Aoto editorial share with you here. If you have a strong interest in big data engineering, I hope this article can help you. If you still want to know more about data analysts, big data engineers tips and materials, you can click on other articles on this site to learn.