It is advantageous to learn data analysis from computer background. Data analysis requires some technical foundation, if simple, you need to know how to use Excel, if complex, you can use Python for data mining and data analysis, of course, you must know SQL statements, and you should practice more. If you know more about deep learning, it will be even more powerful.
There is a computer background, learning Python new language should not be a problem, Python learning materials have a lot of, you can find some of the contents of the full information, first follow the video learning, and so on the practical learning almost, and then find some theoretical books to take a look at.
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For data analysts, learning Python, only need to learn a very simple foundation, coupled with data analysis commonly used packages can be, do not need to learn too deep, such as Django and other Web frameworks and concurrent and other advanced knowledge can be learned, in the process of data analysis is rarely used, including object-oriented knowledge only need to know how to do on the skin.
Data mining knowledge must be learned, how to collect data and from the data to mine the data to help the business is very important, about the data analysis Python library, such as numpy, pandas, etc. is a must write the content, can be combined with some enterprise cases, more to use these modules library, and the better.
Crawler technology is also an essential skill for data analysts, if you do not crawl, a lot of data is difficult to obtain, there is no data to talk about data analysis, the clever woman is difficult to cook without rice.
Machine learning and deep learning can be appropriate to understand on the line, for many data analysts can not be used, seem a little high. General enterprises do deep learning and machine learning have specialized engineers. The larger the company, the more detailed the division of labor. However, these two directions and data mining have a certain relationship, it is recommended to learn more about your future career development is very helpful.
The simplest skills are placed at the end, the general database MySQL or Oracle, for undergraduate computer students have learned in the university classroom. Writing SQL statements is the basic skills, to be able to single-table complex query and multi-table concatenated table query, but also combined with the actual business scenarios, statistical analysis of the tables in the database. For a qualified data analyst, this is a required course.
Excel in the process of data analysis will often be used for the collective amount of data is relatively small, the use of Excel is actually more convenient. Excel in the commonly used functions can be practiced, especially to do basic statistical analysis of the function, they are often used to.