Several mistakes in the process of data analysis

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The role of data analysis Needless to say, in the Web site operations, network promotion and other aspects of the need for data analysis as a support, the so-called MA not move, data first, data analysis is our network to promote the need to master the skills. 28 Push public Service Training 2nd task is data collection and analysis, through the observation of students in the process of data analysis and the final data, found that the most likely to make a few mistakes, this also help you to sum up.

1. No clear analysis of the purpose of the data

We have to analyze a data, first of all to clear their own purposes, why to collect and analyze such a data, but also only clear the purpose of the next to be able to grasp what data should be collected, how to collect data, what data should be analyzed.

2, no reasonable time to arrange

Data analysis should be reasonable to arrange the time, General 11545.html "> We have a few steps to collect data >> collate data >> analysis data >> Landscaping form, before doing this, we have to estimate how long each step will take, Which step is more important, you need to spend more time and so on, before you start to collect data to plan, and then in the process of operation in the time required to complete each step.

3, heavy collection Light analysis

28 Push training Many students have made such a mistake, the task of the time for 3 weeks, but spent two weeks to collect data, and finally there is no time to analyze, close to the last hand to make a lack of analysis of the data. Data analysis should focus on analysis, should be the fastest speed collection of data, have more time to collate and analysis, the final analysis of the data is the most valuable.

4, too much data collection, resulting in inability to collate and analysis

When we start to collect data, it is easy to make a mistake is to see what content is more in line with the collection, such a situation is more and more data, the document in the table more and more, to the last look, they are dizzy, how to finish and analysis Ah! In fact, we have to have a standard when we collect data, What kind of data we need, what data is not eligible, make a preliminary judgment, so that you can reduce the amount of work in the back finishing.

5, do not know what data analysis

This is a more common problem, after collecting data do not know which projects to analyze, which data points to reflect the purpose of analysis. In fact, this is also said the purpose is not clear, it is not clear why to collect this data, this data is used for what use, there will be no criteria, there is no way to find the main points of data. For example, we want to analyze the top ten online travel sites, it is necessary to know what kind of travel site is the best, the best online travel site should have what conditions, these conditions listed, and then according to the conditions to collect the data of the site, and finally meet all the conditions of the site is one of the best travel site.

6, the form is not beautiful, not clear

We do data analysis is generally used in Excel table records, a beautiful and clear table not only allows us to clearly see the focus of the data, to facilitate the search for the data, we collect data in the process, we can improve the collection and analysis of data efficiency. Excel is not skilled students, suggest to find more tutorials, and then more practice, and finally get a beautiful data, they look comfortable.

7, can not adhere to

Data collection and analysis is a very stuffy work, whether it is to collect or analyze, a large number of data, often let people do not feel the clue, the more data, collation analysis of the more trouble, the more easy to make people irritable, will not stick to the halfway. Therefore, do a good job of the above 6 points, that is, clear goals, reasonable timing, grasp the key, know how to choose Data, make exquisite forms, can make you easier to complete the collection and analysis of data.

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