IT Data Analyst

Learning content

1, mathematical knowledge

Mathematical knowledge is the basic knowledge of data analysts. For primary data analysts to understand some of the basic content related to descriptive statistics, there is a certain formula to calculate the ability to understand the common statistical model algorithms is a plus.

For senior data analysts, statistical modeling related knowledge is a necessary ability, linear algebra (mainly matrix calculation related knowledge ) is also best to have some understanding.

2, analysis tools

For junior data analysts, play around with Excel is a must, pivot tables and formulas must be skilled in the use of VBA is a plus. In addition, but also to learn a statistical analysis tools, SPSS as a primer is better.

For advanced data analysts, the use of analytical tools is the core competency, VBA is basically a must, SPSS/SAS/R to be proficient in the use of at least one of them, and other analytical tools (such as Matlab) depending on the situation.

3. Analytical thinking

such as structured thinking, mind mapping, or Baidu brain map, McKinsey-style analysis to understand some of the smart, 5W2H, SWOT and so on that's better. Not necessarily to master how deep and full, but must understand some.

4, database knowledge

Big Data Big Data, that is, a lot of data, Excel can not solve such a large amount of data, you have to use the database. If it is a relational database, such as Oracle, mysql, sglserver, etc., you also have to learn to use SQL statements, filtering sorting, summarizing and so on. Non-relational databases also have to learn, such as: Cassandra, Mongodb, CouchDB, Redis, Riak, Membase, Neo4i and HBase, etc., at least one or two commonly used to understand, such as Hbase, Mongodb, redis and so on.

5, development tools and environment

such as: Linux OS, Hadoop (storage HDFS, computing Yarn), Spark, or some other middleware. Currently used more development tools Java, python and other language tools.

Have skills

Data analysts should learn Exce1, master SQLServer or Oracle SQL statements, master visualization tools.

First of all, Exce1, it seems that this is very simple, in fact, not necessarily. Exce1 not only can do a simple two-dimensional table, complex nested tables, can draw line graphs, Columnchart, Bar chart, Area chart, pie charts, radar charts, Combochar, scatterplot, win Loss charts, etc., and to achieve a more advanced function! .

Including pivot tables (similar to BI's multidimensional analysis model Cube), as well as complex functions such as V1ookup, no big problem to deal with data up to 1 million.

Lastly, many more advanced tools have Exce1 plug-ins, such as some AIMachine Learning development tools Server or Oracle's SQL statements, including join, group by, order various statistical functions by, distinct, sum, count, average , Mastery of visualization tools, such as Bl, such as Cognos, Tableau, FineBI, etc..

Salary

1, the average annual salary:The national data analyst position salary, on average, about 234.060 per year.

2, the annual income range distribution: less than 100,000 accounted for 17%; 100,000 to 200,000 accounted for 36%; more than 200,000 accounted for 47%.

3, the annual salary distribution of different years of service: 1 year ￥ 118,059; 1-3 years ￥ 164,324: 3-5 years ￥ 234,676: 5-10 years ￥ 277,486: more than 10 years ￥ 298.569.

4, the most in demand for data analysts in Shenzhen, Shanghai, Beijing.

5, the highest salary data analyst, the most frequent skill requirements for SQL, data analysis, PYTHON.

6, the highest demand for data analysts industry for the Internet, computer software, e-commerce.

Employment Prospects

In this era of information explosion, every minute and every second in the generation of a large amount of data, data analysts in the massive amount of data to enable enterprises to clearly understand the current situation and the competitive environment, and make full use of the value of the data brought about by the risk of the enterprise judgment and decision-making support.

So the data analyst is not simply an IT person, but a core person who can participate in making decisions about the development of the enterprise.

Successful Internet companies and e-commerce companies, both global and Chinese, are now utilizing data for support and are at the forefront of data-driven business growth.

The development of data analytics in China and the growth in demand for data analytics talent by many companies has led to data analysts being described by the media as "one of the most promising careers of the future".