Big data analyst
One of the most concerned and valued positions in the Internet era
I heard it is mysterious and high-end
So what exactly does a data analyst do?
Next, an article to reveal this mysterious post
Knowledge Post
Big data analysts refer to professionals in different industries who specialize in collecting, sorting, and analyzing industry data, and making industry research, evaluation, and prediction based on the data.
As a complex process, big data analysis basically involves the following links: data acquisition, data processing, data modeling, data analysis, and data visualization.
The big data analysis process sounds very abstract. In order to experience the work process of big data analysis more specifically and clearly, let's walk into a big data analyst's day and find out!
Big data analyst day
8:30 A.M
Image source: Design team of Haidata Lab
A hot day began. Xiao Zhang, a big data analyst at a data consulting company, started a busy day at work. He received a new task in his mailbox-business consulting from a fast-moving consumer company. The fast-moving consumer company’s revenue this year has reduced by 20%, and the number of store visits and product sales has declined rapidly. The company wants to find the causes of these problems and ways to improve it. It is hoped that Zhang’s consulting company can give a complete Improvement plan.
To analyze this problem, you must first make a plan of thinking, and then communicate with the person in charge of the other party's business.
Xiao Zhang took a sip of coffee, tidyed up his clothes, cheered up, and began to devote himself to work. The first step is data acquisition, which requires order data, store traffic data, product SKU data, and related strategies. Ask the person in charge of the other party's business to have a chat, Xiao Zhang thought.
9:00 A.M
Image source: Design team of Haidata Lab
The person in charge of the other party’s business was on the phone for half an hour to discuss in detail, and then he opened the data that was not processed yesterday, skillfully opened the powerful BI system, while organizing the data, thinking about what kind of data is needed for today’s task , What analysis method should be used. Soon, the person in charge of the business arrived.
9:30 A.M
Image source: Design team of Haidata Lab
Xiao Zhang met with the person in charge of the other company, straight to the point, and went straight to the topic. First, he asked the other party's needs, goals, indicator definitions, etc., and asked the other party for nearly three years of order data, store flow data, and product SKU data, and then started I intend to guide the two parties to further think about the decline in the company’s turnover. It is divided into two parts: the number of purchasers and the unit price of the product. It is found that the main reason is the decrease in the number of purchases. Next, the reasons for the decrease in the number of people are initially listed. Product quality decline? Or are there strong competitors to grab customers? Or is this product not in line with customer needs?
The half-hour conversation was very fruitful. With step-by-step questions, communication and derivation, Xiao Zhang finally got more detailed data, and he also had a certain idea for this task.
As a data analyst for many years, I have long understood that communication is one of the indispensable abilities of analysts, especially big data analysts of consulting companies. Efficient communication can quickly obtain information and obtain the required data to complete it more efficiently. task.
10:00 A.M
Image source: Design team of Haidata Lab
Back to the work station, start the second link of big data analysis: data processing. Preliminarily sort out the data, output a string of SQL, get the data you want, open Python, operate it skillfully, think and do it, quickly process dirty data, and get the data format you want.
Professional data analysts need not only efficient communication skills, but also excellent skills. Only by continuous learning and continuous growth can they maintain high sensitivity to the business and efficient processing capabilities.
Finally, the data is processed, the next step is to select the appropriate data model. This time Xiao Zhang chose the more commonly used user portrait model and AARRR model.
Upon analysis, Xiao Zhang forgot about it, and forgot about lunch and lunch break, until the task was completed, several hours had passed.
16:00 P.M
After acquiring the data, cleaning the data, and analyzing the data, what is going to be done is the output of the data report.
Image source: Design team of Haidata Lab
At this step, it is also an important step in the daily work of big data analysts. How to explain these analyzed data and conclusions to customers clearly, so that customers understand current problems, although data analysis is always for consultation It needs services, but how the data obtained can most accurately meet the needs of customers is a matter of consideration.
Xiao Zhang repeatedly pondered the data and the situation of the client company, used product and marketing related knowledge, and initially drafted an analysis report, and communicated the result with his boss, obtained some professional advice, and carried out again modify.
17:30 P.M
The last step of the work is generally data visualization. In fact, most consulting companies focus on ppt production. Making ppt is also not a simple task. Not only must the complicated data and content be condensed in the dozens of ppt pages, but also the ppt must be made generous and beautiful, in line with the aesthetics of the consultant, which requires strong language condensing ability. Also have a certain ability to make visual data charts, typeset and analyze content.
After several hours of refinement, this analysis report is basically complete. At this time, the lights are beginning to shine and the night is getting darker.
20:00 A.M
As the night darkened, Xiao Zhang finally finished his day's work, packaged the ppts and sent them to the supervisor and the consulting party. With relief, he planned to go home and start preparing a presentation to report the analysis results to the consulting party tomorrow. However, in addition to work, there is another big task after returning home to study.
Big data analyst is a lifelong learning profession. Times are changing and technology is innovating. If you don't actively learn, you will soon be completely eliminated by this industry. Xiao Zhang feels that he is not very familiar with visual drawing, so he recently bought a few drawing books for self-study, and he has to learn until the early hours of the morning to sleep at ease.
20:30 A.M
Image source: Design team of Haidata Lab
Xiao Zhang walked away from home in the dark, and the day's work was basically over.
postscript
The most important value of big data analysis lies in business empowerment. The current era is no longer an era of relying on experience, but an era of data. As a big data analyst, when you find that your advice can benefit the other party, and even affect the operation of a company or a government, when you find that you have developed a keen sense of a certain industry in your long-term work intuition. When you find that you have found a unique rhythm of life in your busy work, your sense of accomplishment emerges spontaneously, and you may also slowly start to fall in love with this seemingly boring and trivial job.
The hard work of big data analysis lies in massive data processing, continuous iterative business development, and rapidly developing industry technology. We can't stop, we need to keep learning. This field is updated very quickly, everyone is afraid of being eliminated, and the competition within the industry is also very fierce, so learning has become an inevitable choice to maintain competitiveness.
This is a hot industry that requires passion and hard work. If you are about to enter or have aspirations to enter this industry in the future, you are welcome. I hope this article can increase your understanding of this industry.
If you are still on the sidelines, you can have a deeper understanding of this industry through multiple channels, and you can also express your thoughts in the comment area
If you have entered this industry, then continue to work hard, believe that the data man will do it!
That's it for today's introduction
Do you have any doubts and thoughts about the profession of big data analyst?
Welcome to express your thoughts in the comment section
It's an honor to meet you here
To illuminate one
There are lights about the future!
Image source: Haidata Lab team