1.1. Booming trend
Since the 1990s, European countries began to cultivate a large number of data analysts, until now, the demand for data analysts still focused, but also the expansion trend.
For the Chinese industry outlook and data analysis features, the network side Minco founder Ho pointed out:
First: a huge market, many companies (both cutting-edge Internet companies or traditional) are discussing this, there are real needs and are willing to pay, but patchy not systematic. Currently the data needs of the most intense in the industry are: financial institutions (funds from the bank to the insurance company to P2P company) to advertising and the Internet as the representative of the electricity business enterprises;
Second: still no-show, the company's platform-level model (perhaps often chaotic period before the big market opportunities arise or large);
The third is: technology outsourcing business climate is still not fully formed in the country, for some the ability of technology companies, if the data needs strong words, considering the sound and data security of their own ability, tend not to outsource or external modules, and tend to self-built piece of business;
Fourth: the future of BAT and Jingdong, and 58 drops of taxi and other enterprises, with its own massive data generated, it would be a big player in the data field. But the industry is large and demand, even without start-up companies the opportunity to leave the platform level giants appears, will also set aside a variety of market segments opportunity so that everyone can get their own territory.
1.2. Data analyst occupational requirement
Understand the business: the premise in data analysis is required to understand the business, that is familiar with the industry knowledge, and business processes, the best have their own unique insights, if from the industry knowledge and business background, analysis of the results will only be off-line kite, not much practical value.
From another point of view, to understand the business of sensitive data is reflected. Data analysts do not understand the business, to see just a numbers; understand the business data analyst, sees more than just numbers, he understands numbers, what they mean, know the number is big or small, and pretty good idea , this is the true meaning of the sensitivity of the data.
Understand management: one is to build a framework of analysis requires data, such as data analysis to determine the first step in analyzing ideas need to use theoretical knowledge of marketing and management to guide, if you are not familiar with management theory, then you guidance on how to build a framework for data analysis , as well as follow-up data analysis?
Management on the other hand is to understand the role of the analysis put forward suggestions instructive for data analysis conclusion, if there is no support management theory, it is difficult to ensure the effectiveness of the proposed analysis.
Understand analysis: it refers to master the basic principles of data analysis and some effective methods of data analysis, and can be flexibly applied to practical work, in order to effectively carry out data analysis.
Understand tool: it refers to master data analysis related to the common tools. Data analysis tools is to achieve theoretical data analysis tools, face ever-growing data, the analysis relies on a calculator is not realistic, must take advantage of powerful data analysis tools for data analysis.
Similarly, we should choose the right tool for the study of the problem, to solve the problem as long as the tool is a good tool.
Understand design: refers to the use chart valid expression analysis data analyst's point of view, the analysis results at a glance. The design of the chart is much learning, such as the selection of graphics, layout design, color matching, etc., all need to have a certain design principles.