What is the difference between data analysis in actual work?

1. Data Mining and data analysis are on! Actually working! Is there a big difference or even a big difference? I know some definitions. For example, data analysis focuses on statistics, while data mining focuses on classification and clustering, and information extraction. But is it often done in two aspects in actual work? Unclear.

A: What are the differences between the first question mark? The second question mark, who is doing this in actual work?
Some tips: in actual work, data mining usually follows engineers, while data analysis is analyst in English. Generally, a person, analyst, or mining engineer will not be two roles at the same time, but at least focus on them.

2. Some organizations (Internet and software) Looking for data require programming, such as Python, R, and hadoop. Some seem to require applications, such as Spss, SAS, and Modeler. Is it true that some people in programming can make the website respond dynamically, while those in the application work to improve the operation and business status through understanding and analyzing? Are some companies calling this role a demand analyst or business analyst?

A: For data users, this word reflects that you do not know much about the actual work. What is "data person "? There are many aspects of data, so there are also many people. My understanding is that the programming you mentioned is more biased towards the construction of the base layer. The application you mentioned is based on the base layer and belongs to the scope of analyst.

3. Do companies really pay enough attention to their analysis structure for those who have applied the questions and questions? What departments are these employees generally in? Are there many positions?

A: Is the company paying enough attention to the analysis result? This is a big question, so I am very grateful to you. Let me deconstruct: who represents the company? Business side? What level of people does the business team have? Then, if your analysis result is to report to the General Manager of the business department, will your analysis conclusions really help the general manager's work? If the answer is yes, I think the general manager will pay attention to it. However, if your analysis results do not reach the level of attention of the general manager, you may not have the opportunity to share your conclusions with the General Manager, or even the general manager will not buying, do you come to the conclusion that this company does not pay much attention to your analysis?
The distribution of these employees is usually like this: large companies have independent bi departments (Business Intelligence Department), which are concentrated here; some small companies directly belong to the business department, such as Operation Department, sales department, and even finance department.
Are there many positions? This problem roughly calculates the ratio of analysts to the service department at. If the number of analysts in a company is 200, the analyst team is about 4.

4. Do you think the entire data analysis/mining is a conceptual hype, or we have encountered the big data/cloud era, so there is a great prospect for application?

A: It's a big question. The prospect is nothing more than the hype of concepts. You can always tell that future decisions are increasingly dependent on information, that is, data is increasingly dependent on data output (data is an important source of information ). The conclusion is certainly not too broad. The question is, what is the relationship with you, which has a great prospect?

I tried my best to answer your questions one by one in Q &. But in fact, from your question, I can feel that your interest is actually quite vague. You used to say "I am particularly interested in this direction". I said that I am especially interested in psychology. What are you interested in? If you just buy a book from a counselor and flip through the contents, you will know the structure of the sub-terms below, and further in-depth and in-depth development, there are great differences. After reading the book, you are still confused. Are you still interested? What are you interested in? I suggest you seriously consider this issue.

In this case, you may still be confused. Let's read some blogs of cool people in this field. First, you will learn from the real person, and your doubts may be uncovered. Hope to help you.