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What's the difference between Python Data Analytics Post 10k and 30k Plus?

May 29, 2021 Article blog

Python Data Analytics is a very popular industry, but there are also 10k to 30K, so do you know why the difference between the two is so big? One day, Ali Jiu's product manager found that the retention of recent new users is relatively poor, find data analyst Xiao Wang: Xiao Wang ah, recently the retention of new users is relatively poor, you can help analyze the reasons?

What would you do if it were you?
01 The data analysts I've met generally have these processing methods:
The first category: primary, will only passively take numbers.
Check the line of business DAU, jump out rate, retention time and other data, to the product manager, completed.
This kind of data analyst is the most common, but also the work status of many of my readers, characterized by: no way to solve business problems, business units lack of data, I take what data ... O ften called "tea mushrooms / cousins / cousins", most of their salary is less than 20k.
The second category: intermediate, to solve specific problems.
Using a top-down way of thinking to analyze, by doing user portraits - looking for differences - differences quantified into indicators - problem assumptions - improvement schemes - validation, found that four or five-tier city users do not like the current cold start push products, is the real reason for the new user retention gap. T o be able to do this, 20k should be no problem up. Category 3: Advanced, guiding the business.
In addition to completing this data analysis, it is possible to understand the average data of the next industry, look at the model of competition, and then chat with the front-line business, chat with the leaders of different departments, analysis of whether this is a data problem?

Finally, to help you sort out how many roads, how to go this way. To be able to participate in company decision-making, the level of wages certainly need not be said.
Who do you think the product manager will listen to? W ho will the leader consider when he or she gets a promotion and a raise? /b10> 02 Data analyst these three abilities, you have to have If you are still in the extraction stage, do not panic, this is a necessary process, but after three or five years of work, but also called cousin cousin, it is dangerous, you need to immediately improve these three capabilities: data analysis tools, this is the basis need not say. /b13>But don't think it's just Excel, SQL, and you'll get paid more, and we recommend that you learn all the commonly used data tools like Python, Tableau, powerBI, and so on. ed. /b14>To this stage, just master the tool is certainly not possible, need to master the data analysis methods and models, at least know where to bury, how to build a long-term statistical model. ue. /b15>Only by grasping the nature of the business, and analyzing the conclusions and reports, can you be constructive, influence decision-making and even improve performance. Reprinted from: Rookie Python
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