The internet is a time of change, data analysisprobably the most popular skill at the moment, and now almost80% of the recruitment requirements, the interviewer is expected to have the ability to analyze data.
The same goes for interns who just came out of school:I heard from work yesterday.2 interns are discussing data acquisition and analysis issues. Very frankly speaking, an internship of the small white, do not need to know the data, they only need to be responsible for pulling the basic data, fill the base of the copy, do the most basic implementation work, which for them is the biggest growth. But they are talking about data analysis, and even the collection of things. It surprised me a lot.Does the Internet really change so fast? I'm a fast worker .5 years of people, access to data time is only 1 years. It is clear that data is a self-evident place in the Internet. So, from small white to Daniel, began the data learning path.
generally speaking, data analysis is divided into the following3 levels:1, Rookie level:little white, or a little bit of experience (0-1 years of work experience), the first question that lies before you is to give you a bunch of data to analyze and solve problems.so we all rely on"Every eye of the flesh", read reading is the amount of reading, see conversion rate or conversion rate, do not comprehend by analogy the data, so it is important to improve the ability to analyze problems.2. Veteran level:have a certain experience, or a careerAbout 5 years. They already have their own familiar tools, and methods. can also take the initiative in the work through the data to find more real problems, like the sun monkeys have "eyes", a glance can see through the truth behind.
3, the old driver level:generally are directors, managers, they usually have7-10 of experience. They usually draw a pair of "clairvoyance" from the summary of a large amount of data, and make a plan for effective data funnel. Although they have their own advantages in data analysis and collection.but basically (including working longer) after data acquisition, data analysis can not be used in the most intuitive and accurate way to express. especially the novice, particularly easy in this regard lead to work results are not recognized, even criticized.
It's better not to do such a job. In general, data is already an indispensable survival skill for the internet in hurricane showers. In this imperceptible change, the new ecology of the internet is coming. Whether it's a small white, or a working experience, data analysis tips here, the evolution is faster than you can imagine!PublicNumber:Maibanzhang(material from the network, not original, if there is similar, please contact delete)
I didn't see the data analysis, now the data analysis and the boss can not see me!
