I have been doing data analysis related work for more than half a year now, and today I will talk about my experience along the way and my daily work. 
1.What skills do you need?
(1) Master SQL skillsWhy is SQL the most important?As far as my current work is concerned, almost more than 90% of the work must use SQL, and I can't continue to work without SQL. Generally speaking, the company's business data are stored in the database, which is convenient for management and preservation, and SQL is the language for operating the database, which is the basic quality necessary for dealing with the database. The collected data is stored in the table of the database, and these data are called the raw data of the business database, which obviously cannot be used directly. This is where SQL comes into play. For example, if you need to retrieve data at work, you need to be able to use SQL to analyze the data you need for your business, and then export it to Excel. The most important thing in SQL is to keep practicing, learn the basic SQL knowledge points in one line, and then find common interview questions to practice more, so that even if there are SQL written test questions in the interview, you will not panic. (2) Python is a plusMy current job can't be done without python. For example, if you want to make a report for a related business, you need to write python to automate the processing. Or because of business needs, you need to connect two tables across databases (between different databases), which also needs to be done in python. So, to what extent does python learn?The basic syntax of Python and the commonly used data analysis packages (pandas, numpy) should be used. (3) Data visualizationAt present, the visualization tool used for work is the open-source Superset, on which all reports are presented for business personnel to use. Each company may use different visualization tools, if you want to learn Excel, Tableau, Power-BI and other tools, learn one, other tools will naturally be. 2.What does a day-to-day job do?
Every morning, I will check the email to confirm whether the data report sent to each business department has been successfully sent. In the visualization tool, see if there are any anomalies and omissions in the data of each related report, in general, if there is a problem, the product manager will send a message as soon as possible, but it will be better to check it in advance. If there is a problematic indicator, it is necessary to use common analysis methods to find the cause of the problem and make recommendations.
Then the requirements of the business modules for which they are responsible are completed according to the schedule, and the requirements are generally confirmed at a meeting every Monday. Each requirement should be carefully read and fully communicated with the product manager to ensure that both sides have the same understanding of the requirements. After that, I started to write SQL or Python. If you don't understand the technology, ask your colleagues to help, and finally ensure that the relevant needs are completed on time. The product manager checks the data for accuracy, completes the review, and the requirement is closed. Finally, interview data analysis has a considerable probability of taking the SQL written test, so you must pay attention to it, and then keep your mentality stable, and say your advantages, under normal circumstances, you have basically passed the interview after the SQL written test, I wish you all those who want to use data analysis to enhance their competitiveness in the workplace can succeed. List of high-quality authors