As the saying goes: "Ten skinheads nine rich", now "skinheads do database."But why does this industry, which has put the hairline at risk, have so many international students desperate to drill in every year?

Today's line has an inside look, and we've brought in three "old drivers" in the field of data analysts to unlock the mysteries of the data analytics industry.

They are:

Robin

Graduated from the University of Maryland Business School with a major in Information Systems

He currently works in Amazon's Business Development Department

Grassland.

Graduated from Columbia University with a degree in data analysis

He was in charge of Beijing Normal University

Data analysis for online education platforms

Silk

Graduated from The College of William and Mary with a degree in Business Data Analysis

He now works for Tech firm as a business data artist

Insider No.1

Can I become a data analyst?

Let's start with Cop, what exactly do data analysts do?

Mainly responsible for collecting, processing and executing statistical data analysis, the use of tools, extraction, analysis, presentation of data, to achieve the commercial significance of data, business understanding and tool application capabilities.

Data analysts, as the name suggests, are analyzing data based on a variety of analytical methods, but not only that, but also to dig and present surface data in greater depth, helping companies make important business decisions. In general, the task of a data analyst is to clean, analyze, and visualize the data.

Because the data involves a wide range of aspects, whether it is e-commerce or computers, in fact, contains a lot of data. So the data analysis industry is relatively wide, but we can see the commonality of data analysts, no matter what profession, they will generally learn:Mathematics, statistics, information management, computers, e-commerce, marketing, quantitative economics and so on。 If there are hunting students involved in these aspects, you may wish to explore your interest in data analysis and talent Oh!

Insider No.2

Data analyst's day-to-day

Data Analysis Four!Data analysis in different businesses and industries will have their own corresponding characteristics, but in general, data analysis will have a determination-decomposition-evaluation-decision,four steps.

Are you sure. - That's what Prairie calls cleanup data, and analysts need to get enough background information before they can start analyzing it, let's do itBe clear about what problems you want to solve with this dataand then select useful data and available resources.

Decomposition. - Corresponding to TheUre Engineering described in the Prairie.Divide large problems into manageable, solveable small problem groups, and then decompose the data into smaller groups quickly for decomposition and extraction.

Evaluation. - Why run the model? Because there needs to be evaluation and comparison, for examplePrice comparison, sales comparison, competitor comparison, and Robin said the strategic development of the comparisonto see which product is better for you.

Decision. - Based on the analysis of the data,Explain it to the company or the customer, the analyst based on what information, what conclusions, and then give recommendations.

Because data analysts are presented with a clear and data-backed report to business decision makers after data mining and presentation, data analysts are not simple technical staff, but can play a major role in enterprise decision-making.

As for AI, which has been hot in recent years, although computing speed will be faster than human computing, AI is a mode of thinking written and given by humans, and data analysis needs to combine a lot of industry knowledge and understanding of data indicators. Because data analysts have this decision-making capability, AI AI is not an easy replacement for the profession.

Insider No.3

Graduates who want to be data analysts have seen it!

Data-related experience is important!Whether it's an internship in a large or small business, or even a startup, try it. Regardless of the size of the company, the position is high and low, the accumulation of experience is the most important. When you have a certain experience, understand the operation of the industry, it is relatively easy to enter the door! As mentioned above, each industry area has a different background, if combined with the individual's previous experience background to do the corresponding data analysis of the industry, but also become your advantage!

It's important to constantly update your knowledge base!Because of the rapid updating of knowledge and information in the data analytics industry, to become a data analyst, you must expose yourself to the latest technology and knowledge in the industry at any time.Race against the speed of knowledge renewal!

Industry resources matter! Students can have more contact with projects in the industry. If the school does not provide the project, you can go to their own professors, generally speaking, professors are the industry leader, and their own hands are related resources.In the data analysis industry, experience is more delicious, and seeking more data analysis experience in learning will help future job search.

Speaking of industry resources

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