In recent years, "big data" seems to have become a more and more fashionable word, it is no longer only the Internet industry to talk about the topic, "big data" has begun to be more and more common people are familiar with, big data has also penetrated into our lives. The newest addition to the list is the newest addition to the list, which is the newest addition to the list.

The profession of data analytics is also one of the most promising fields at present, and more and more people want to invest in it, and in the era of big data with explosive data growth, there is a surplus of data and a shortage of talent. Data Ocean With years of experience in the field, the students summarized as a data analyst should know the nine questions:

1, how to do a good job of data analysis?

The growth of analysts is through the "dry", "thinking", "boiling" out. Dry: do more. What are the temporary needs. You have to do a variety of analysis; think: you in the process of dry, to think, summarize, only this you can precipitate. Boil: through the accumulation of time, your business sense, data analysis thinking, skills are improved, wide accumulation of food, slow king, to realize the thick and thin.

2, how to do a good job of data mining?

Data mining and data analysis in my opinion, are the realization of the value of data "tools", "way". Data mining relative to data analysis, the entry threshold will be higher, for data mining methods, mining tools require more. But do a good job of data mining, reference data analysis.

3, what type of books need to read?

Very much from just do analyst friends, but like to ask: I want to do a good job of analysts to read what kind of books? The logic behind this is not to say that you read the books recommended to you by others, you can become a very good analyst.

My point of view is: the book is to be sure to read, and have the opportunity to read more books. But make sure you understand what value you place on reading books.

But data analysis is more dry, practice to grow.

4, good data analysis needs what kind of skills?

I want to do data analysis, must know SAS, SPSS, R? If you don't go for modeling.

Basic statistical knowledge must be mastered, but analysts are still mainly SQL + EXCEL + PPT to complete an analysis report.

5, what kind of specialty can do data analysis?

Now most of the recruitment of data analytics are required: computer, statistics-related majors. But I believe that the future of data analytics recruitment will be more and more wide range of specialties, and many management (marketing, management, intelligence, etc.) professional graduates will be more popular. Because when we understand more and more deep understanding of data analytics, we will find that the core ability of data analytics is still in: analyze data, and then combined with business.

6, the value of data analysis?

Based on historical data, to tell the relevant people how the business situation, combined with the understanding of the company's business model, together with the development of related strategies to help the company to achieve business goals.

Based on the company's internal and external data, combined with the analyst's understanding of the company's business and industry trends, the company and industry trends are proposed to provide a reference for the company to develop appropriate strategies.

7, data analysis, in the end, what data is analyzed?

Analysis of the company's internal and external data, internal data are the following categories (e-commerce, for example):

1, traffic data or website clickstream (log) data.

2, order data.

3, product data.

4, member data.

5, supply chain-related data.

6, customer service data.

Different companies have different granularity and completeness of data collection. Whether all companies have to collect all the data, my view is: if allowed, of course, the more the better. But a lot of time is to analysts to assess which data needs to be collected, save how long the data. Analysts must use a certain sense of ROI.

The kind of data have not accumulated much, claiming to be a big data company, claiming to suggest a competitive advantage through big data, do you think it is possible?

8, data analysis has several roles?

Data analytics: assistant analyst, analyst, senior data analytics/data analytics specialist, business analyst;

Data product manager:I especially like this perspective, I think of the real data analysts, there should be product thinking logic. Because no matter what you are doing statements, reports, systems, that even a simple data needs, you can be understood as a data product. (What is a product, the product is to solve the problem of the target user. Please analysts all keep this in mind.)

Data mining: data mining engineers, senior mining engineers;

9, what kind of people are suitable for data analysis?

In addition to some of my previous articles discussing the need for relevant and basic skills, perhaps the following is more important for a data analyst to grow:

1, see the data have a sense of excitement. There is a sense of excitement that you are interested, that means very will have the will to analyze the data well.

2, willing to learn. The content of your analysis will never be the same, even if you analyze the theme is relatively fixed, but the business is changing, you need to constantly learn the business, with different people to communicate, absorb the views of others. So analysts must have a learning attitude.

3, strong logical thinking. Data analysts want to put your analysis well, must have a conclusion thinking.

4, expression and communication. Because the realization of the ultimate value of data analysis, generally speaking, will not be the analyst himself to develop or implement. So you must be very organized, logical and clear to others to express, so that the business side to recognize the value of your analysis results, so as to influence the business side to be willing to use the views you get from the data.