Introduction of data analysis refers to the use of appropriate statistical analysis methods to collect a lot of data analysis, extraction of useful information and constitute the conclusion of the data to the specific study and summarize the process. In practical applications, data analysis can help people make judgments in order to take appropriate action. When faced with massive amounts of data, the power of data analysis has become a problem for analysts. So, why data analysis? How to improve the efficiency of data analysis?

Why data analysis?

1, the evaluation of product timing

Products conceived in the early stages of the necessary demand research and market research is particularly critical. Evaluation of the timing of the product evaluation of the later product design and iteration is critical, and even said that the resolution of the future of a product and the core concept.

2, analyze and solve the problem

The product is in poor condition, there must be a reason. It is impossible to imagine imaginary problems, must respect the objective reality. Then only through the necessary data experiments can be traced back to the source of the problem, and then develop a reasonable solution plan to completely solve the problem.

3, support for operational activities

How about the role of your product features on line, plan A and plan B which is better? All these questions involve a "standard" problem. Judge the good and bad of a problem, I'm afraid the most reliable is the data. As I once said, "People are unreliable; they are always willing to believe what they want to see." As long as you give real, solid, objective facts - data - you can make the most realistic judgment of a specific activity.

4, guess the optimization of the product

The results of data analysis can not only react to the status of the previous product, the so-called hindsight data; it can also give a product in the future time period may be encountered in the problem, the so-called foresight data. A real data indicator must be actionable. Both hindsight and foresight data are actionable, the difference is that foresight data can guess what will happen in the future, shorten the iteration cycle, and fine-tune the process.

How can I improve the efficiency of my data analysis?

One, the intention of clear analysis

Data analysis of the data source is often huge and unruly, at this time it is necessary to clarify the intention of data analysis. What kind of results do you need to show through data analysis. Data needs directly from the final results of the analysis, if you have now comprehensively planned what analysis to be done and what results to produce, then you will know what the data needs are.

Second, the analysis of ideas systematic, logical words

In data analysis, you can draw on management marketing and other theoretical knowledge, open the analysis of ideas, data analysis to form a systematic, logical analysis model.

Three, master the effective analysis method

Skillful mastery of the general process of data analysis, master the analysis method. Theory and practice combined to cultivate data analysis methods and data before the logical ability to control, comprehensive and deep understanding of the value of data, scientific data analysis work.

Four, choose the appropriate analysis thing

A suitable data analysis thing is to assist the data analysis of the tool, but facing a lot of analysis things on the market, how to find simple and easy to use analysis thing seems to have become a problem for business people. Big Data Magic Mirror as a mobilization of data analysis and mining one of the visualization software, ease of use is very strong, just a simple drag and drop to complete the data analysis work.

Fifth, speak with charts

Simple and clear charts can help better show the data results and find the problem. In the process of data analysis, charts can help clarify the analysis of ideas, jump out of the analysis of bottlenecks.

Six, a variety of visualization

Following the development of information technology, data blowout era brings massive amounts of data, the previous general monotonous presentation is now unable to meet the demand. Together with the enterprise, the clear and diversified data can better explore the problem, and bring scientific basis and reference for enterprise resolution plan. Big Data Magic Mirror has more than 500 kinds of visualization effects and the baking speed reaches the second level.

Seven, concentrate on the spirit of regular rest

On the relevant business personnel or big data analysts, efficient and focused analysis of the moment is limited, perhaps concentrated in a few hours, so in the data analysis work should be reasonable allocation of time, regular rest, relaxation of the brain.

The above is the editorial today to organize and share with you about "why data analysis? How to improve the efficiency of data analysis?" The relevant content of the hope that it will help you. I believe that in order to make a mark in the big data industry, you need to take part of the high gold content of the data analyst certificate, so that there is more core competitiveness and competitive capital.