A data analyst trained by a data analyst is a data engineer who specializes in collecting, sorting and analyzing industry data and making industry research, evaluation and prediction based on the data. Big data engineers trained by big data actually have many aliases. Data mining engineers, big data experts, data researchers, user analysts, etc. Both are titles that often appear in domestic companies. Big data engineers are a group of people who "play with data", bring the commercial value of data into play and turn data into productivity. The biggest difference between big data and traditional data is that it is online, real-time, massive, irregular and irregular, so it is very important for people to "play" these data.

2. Development direction

The development directions of data analysts after training are: market research direction, data analysis/mining direction, data engineer direction and so on. The development directions of big data engineers in big data training are: chief data officer (CDO), marketing analyst/customer relationship management analyst, data engineer, BI development engineer, data visualization and so on.

Step 3 have skills

Data analysts and big data engineers need similar skills, such as:

(1) data and data warehouse data are the basis of data analysis, the database is the carrier of data, and the data warehouse is a thematic database.

(2) Reporting, the original BI method is sometimes simple and effective, but it seems that there are many problems to be considered to make an excellent report.

(3) As a supplement to the non-intelligent BI of reports, data mining should theoretically belong to a kind of machine learning, with a little computer self-learning ability.

(4) Algorithm With the rise of object-oriented programming method, "program = data structure+algorithm. If you want to be a top data analyst, knowledge of algorithms and data structures is essential. Search, sorting, trees and graphs are classic because they are simple, effective and universal.