What python data analysts need to learn

Python data analyst. Nowadays, big data analysis is extremely popular. From a development perspective, python data analysts are very promising. But not just any company can do big data analysis. There are several issues to consider when doing big data: whether the source of big data is comprehensive, what to analyze, who will use it, etc. Of course, if you can find a company that can do big data, the salary will still be considerable. To be a python data analyst, you have to learn some things. Otherwise, if you can't be an analyst, you may just become a programmer and help others achieve the results of analysis.

#First: statistical knowledge. (Recommended learning: Python video tutorial)

This is the shortcoming of a large number of big data analysts. Of course, what we are talking about here is not just some simple statistics. Instead, it includes mean, median, standard deviation, variance, probability, hypothesis testing, etc. with time, space, and data itself. It should be almost the knowledge of advanced mathematics in science and engineering, or even a little higher. You must be able to model, otherwise if the results you analyze are far from reality, you will probably be packed up and left in a few days. Of course, being an ordinary big data analyst will not involve in-depth advanced mathematics knowledge, but to be an awesome big data analyst, you still need to learn and learn again.

Second: Many people don’t think of it. You’d better get familiar with EXCEL.

Of course, you don’t need to master the advanced knowledge, but you also need to master commonly used functions. For example, the key points include but are not limited to sum, count, sumif, countif, find, if, left/right, and time conversion. Pivot tables, various charting practices, etc. If the amount of data is not particularly large, Excel can solve many problems. For example, filter some stolen data, sort, select data that meets conditions, etc.

Third: Practice analytical thinking.

For example, structured thinking, mind mapping, or Baidu mind mapping, McKinsey-style analysis, it would be better to know some smart, 5W2H, SWOT, etc. You don’t have to master it deeply and completely, but you must know something.

Fourth: Database knowledge.

Big data Big data means that when there is a large amount of data and Excel cannot handle such a large amount of data, a database must be used. If it is a relational database, such as Oracle, mysql, sqlserver, etc., you have to learn to use SQL statements, filtering, sorting, summarization, etc. You also need to learn non-relational databases, such as Cassandra, Mongodb, CouchDB, Redis, Riak, Membase, Neo4j and HBase, etc., and at least know one or two commonly used ones, such as Hbase, Mongodb, redis, etc.

Fifth: business learning.

In fact, for big data analysts, understanding the business is more important than understanding the data. Data analysis plays a very important role in how the industry's business develops. If you don't understand the business, the results of your analysis may not be what others want.

Sixth: Development tools and environment.

For example: Linux OS, Hadoop (storing HDFS, computing Yarn), Spark, or some other middleware. Currently, many development tools, python and other language tools are used.

In short, it is quite brain-burning to be a senior or director-level big data analyst. If what you want to learn and understand is just pure data, then learning business and statistical knowledge is essential. If you are a practical big data analyst, you may only master certain parts. For big data development engineers, it is basically necessary to master the development environment, development language and the application of various charts, which is also satisfactory. After all, a company needs teamwork, and one person can come up with analytical products if they understand a part of it. Decide on something and do it! The harder you work, the easier it becomes, and the harder you work, the better you get!

For more Python related technical articles, please visit the Python Tutorial column to learn!

The above is the detailed content of What python data analysts need to learn. For more information, please follow other related articles on the PHP Chinese website!