Some time ago, I chatted in the peer group , Talking about the problem of industry salary , The concept of big data is hot these two years , Data analysis has also become a hot position , From the recruitment website , The average monthly salary of data analysts is 10k-20k between .
Data analysts from some large factories have arrived 30k one month , According to this data, data analyst is a well paid profession , But from the group discussion, I found that , The reality is not so good , Most people don't get paid 10k, Even some two , Data analysts in third tier cities earn only 4,5k.
Why is data analysis the same , There's such a big pay gap ? Access , clean , Visual analysis and other skills should be mastered , Why do I get less than a month's salary , Many people have raised such questions .
Let's look at a monthly salary 30k Data analysis of position Recruitment Information :
Salary market given by Ctrip 20k-40k, Work experience requirements are 3-5 year , It can be seen that work experience is very important for data analysts , But I still have jobs around me 3,4 Even 5,6 Data analyst in , Still in place , Pay to the day 15k, Why 3 The number of analysts with annual working experience is not valuable ?
Gap one ： Business thinking ability
Let's take a look at its job description ：
Comparison of monthly salary 8k Data analysis of the work content and this monthly salary 30k Job description , It's easy for us to see the gap . Most data analysts' daily work is based on the needs of the business or leaders , Take data and make report , Business allows analysis , What data should leaders give , It's like a porter , A tool man in the eyes of business and boss , Low value, low salary .
And the job description of Ctrip's Recruitment Information mentions “ Provide relevant data to business department , Guide business development
”, Pay attention to the second half of the sentence , I often mention it in my articles , The value of data analysis is to drive business development , Help business solve problems , How nice the report is , No guidance for the business , Such data analysis is done for nothing .
for instance ： The boss told the data analyst ： I want to see the sales of the stores in this city this week , Give me the results in a week .
a monthly salary 8k Analysts of A Will do so ： Retrieving store sales records , Data of cost management and other modules , Export data , utilize Excel perhaps python tool , Make data visualization chart , Add two sentences of data interpretation to the report ： Goods sold 100000 piece , income 700 ten thousand , Net profit 180 ten thousand .
Senior Data Analyst B Will do so ： First, study the company's development strategy this year and the business adjustment strategy recently adopted by the boss , Learn that the boss wants to reduce the operating cost of the store recently . Transfer employee attendance , Cargo storage record and other data , Using comparative analysis to find out outliers , And match specific business scenarios , come to conclusion ：A Stores in the second quarter in the off-season , Should be reduced 30% Personnel input ,B Utilization rate of cold storage is lower than average , Cold storage structure should be adjusted .... Through these initiatives , Total cost expected to decrease 15%.
If the boss wants to A,B Choose a promotion and raise , You don't have to think about it B Of .
Gap 2 ： Tool capability
The core ability of data analyst is thinking , Sub core capability is tool , As the saying goes, a good weapon is needed in war . For junior data analysts , It's basically for beginners Excel, As long as the function is familiar , The pivot table works well , Do some regular data analysis report or nothing .
But in the actual work , Light meeting excel No way , Increasing data for enterprises , Large amount of data , And it is distributed in various business systems , Optical access is a huge job , And large amount of data
Excel It will take half a day to open , Let alone the complicated analysis operation . Therefore, data analysts need to master some professional data analysis tools , improve work efficiency , For example, common website analysis GA/Omniture,SQL Access platform (presto,hive etc. ),FineBI Business intelligence tools, etc
In this recruitment qualification , The first is to master at least one front end BI tool , For senior data analysts ,BI Tools are really a good choice . Powerful data analysis performance and visualization , And perfect enterprise level data authority management , Give Way BI Tools have become the choice of many enterprises , Especially the Internet factories like Ctrip .BI It can greatly liberate the work of data analysts , Whether it's business analysis or decision management , Take the domestic ones FineBI In terms of , It can optimize data analysis from such aspects ：
1, Support multiple data source links , Breaking the information island between enterprise systems .
Generally, we need to use data scattered in various systems of the enterprise for data analysis , Before analysis, data should be fetched and exported to each system , And then excel analysis , Very complicated , If you meet a weekly newspaper , The need for repetition like daily newspapers , You have to export it over and over again , Update data , Very inefficient .
and FineBI You can directly connect with the database through the built-in engine , support 30 Multiple mainstream databases and Excel data set , It also provides two modes of real-time and data extraction , Like the weekly , Repetitive needs like daily newspapers , Make a template directly , You can get the desired report by filtering the date through the date control , No need to update data repeatedly .
2, Simple and convenient data processing , Double efficiency
In the process of data analysis , Except for the trouble of fetching data , Another headache is data processing , It often takes half the effort .
Let's analyze the sales details of the company's products , Then analyze the characteristics of purchasing users , Adjust sales strategy . We need to base on the sales list data , Calculate the corresponding analysis index , Such as the consumption frequency of each person , Maximum amount of single consumption , Last consumption interval, etc . More complicated , According to the same type of products , Do correlation analysis and horizontal comparative analysis with competitive product data . use Excel It's a huge project , use excel To do data calculation, a large number of complex and tedious plane cell formulas are needed , And it's easy to lose all your efforts if you make a mistake in one step
If you use BI It's a lot easier to make tools ,FineBI New columns are provided in the self-service dataset of , Group statistics , filter , sort , Merge up and down , Data processing functions such as left and right merging , And each operation can preview the results in real time , Error Prevention , You can also add a single historical operation , Delete and modify , Very flexible .
3, Drag and drop exploration and analysis , What you see is what you get , Visual effect
After data processing, the next step is data visualization analysis ,BI Drag and drop exploration and analysis of tools , Visual charts can be generated automatically by dragging fields with the mouse , Make it easy for users to realize real-time insights and insights into data .
And it's worth mentioning BI Powerful visualization of tools , On the market BI The tools are basically built-in with rich visual charts , Easy to make eye-catching visual reports . Usually we use Excel When visualizing , If you want to implement some advanced visualization charts , For example, data map , Dynamic reports and so on , You need to use PivotTable and some chart plug-ins , And the steps are complicated , And these are FineBI
All built-in , It can be used directly
In addition to providing rich chart analysis ,Finebi The dashboard also provides users with flexibility to layout data charts , Generate story based visual reports , So as to achieve the purpose of effective communication or data reporting .
in addition to , Another big move is to make and manage cockpit for leaders , Like the following , Put all the data concerned by leaders on one screen , Real time data presentation , Leaders can monitor key data in real time , Discover problems in time , And it can also be drilled , Linkage to further analyze and view the cause of abnormal data ：
Can make such a cockpit , There must be no problem with promotion and raise .
Gap three ： communication skills
If business thinking OK, The hard strength of tools and skills is also impeccable , Still can't get the promotion and raise , So the problem might be communication skills
upper . Data analysis technology is not good , Good communication ability and academic ability are also the key abilities for a person to mix up in the workplace , Data analysis needs to understand the business , Looking for data , Presentation Report , Dealing with people from different departments , Communication skills are essential , For senior data analysts , Also need to be responsible for the project independently , Or cooperate with the product , Besides strong communication skills , Some project coordination capabilities are needed .
If you find yourself and your peers growing apart , We might as well reflect on ourselves from the above three aspects , Continuous improvement and progress . Hope everyone can become an excellent data analysis expert !