Writing points: Many students who do data analysis have no project experience or serious modeling. They work as human SQL machines every day and run a lot of numbers. At this time, you will feel as if you are busy every day, but you don’t know what to do. So it is easy to Saudi Arabia Mobile Number write a few words in a hurry.
There are only adjectives such as “busy”, “tired”, “many”, “a lot” and “fucking too much”. This kind of report is the most likely to be criticized by the leaders, and there is no benefit other than being scolded. Everyone should take it as a warning.
Second, the crossover type
Usage scenario: Students who have no desires and no desires, and who have handed in their homework.
Writing point: If you just want to cross, remember this sentence pattern: I + completed the +XX task. Get it done! In this way, I can express to the boss intuitively and clearly: I have finished the work that I explained. In order to overcome the problem of version 1, Therefore, it needs to be classified.
The five most common outputs of data analysis are: temporary data access, reports, special reports, models, and data Saudi Arabia Mobile Number products. It can be divided into five parts to write. Each job has four states: new, updated, optimized, and iterated (deleted/merged), which can also be written separately. In this way, the seemingly chaotic daily work can be clearly classified.
Some classmates will complain, saying: I have done classification and found that 90% of my work is to update reports, and output reports in a fixed format day by day by day by 365 days… This is really Saudi Arabia Mobile Number worthless, can’t write it Let’s go! Yes, Just give up this year’s performance appraisal, and ask yourself next year why you are so content with the status quo, and don’t want to toss something about your grades.
Three, the icing on the cake
Writing point: If you want to add icing on the cake, you can’t just say: What work did I do. Instead, I have to say: What value have I created. The same is the work, the leader has always been more concerned about: who has the greater output. But data analysts are not the same as sales, operations, and product managers, and have unique ways of writing.
So you can’t just blow it like sales: I made 10 million for the company! The biggest difference between data analysis work and operations is that data analysis is a support position. It is not as high-profile as operations and can boast: our activities attracted 100 million clicks and drove DAU to increase by 30%.