With the rapid development of society, the rapid popularization of the Internet, data analysts have become the most sought-after, the hottest profession in this era, so how can we become a qualified data analyst? Yinchuan IT training / that need to have the following five skills! First, skillful business skills only in the field of practice have done data analysis work, only to understand that all the analysis of the top priority is business knowledge itself.

But the learning and mastery of business knowledge is the need for a certain amount of time and experience accumulation, training a data expert, the need for a long time cycle, far more than the basic skills described below.

Data analysts are actually business experts on top of a deeper level of thinking and summarizing, otherwise, who guides who is a problem.

Two, meticulous thinking ability data is always there, it will not talk, you not only want to understand it based on the business ability, but also learn to deduce and analyze, from which to find the law, and quickly locate the key attributes and determinants of a business problem, to form their own unique insights, the so-called meticulous, watertight, no thinking logic, no data analysis.

To form unique insights, it comes from the individual's continuous learning and thinking, where learning is more emphasized across fields and professions, and thinking is more emphasized to develop the habit of thinking.

Thinking itself is a practice, it can be more systematic and in-depth knowledge, data analysis is used to a certain extent to validate the ideas and inspiration, "data analysis" is never "data analysis" itself, but with the "data analysis". Data analysis" is never "data analysis" itself, but to "data analysis" as a means and appearance, a deep understanding of the business, thinking and judgment.

Three, good communication skills data analysis throughout the BIT, data, technology, business throughout the chain, data analysts will BIT ultimately transformed into the language of decision makers to understand the process across a very long time, you need to face different positions, encountered different roles, the use of different languages, to express your requirements and access to the things you need to become a bridge between the data and the business, there is not enough! communication skills is difficult.

Four, systematic data learning Of course, most data analysts may not need to carry out systematic data learning, anyway, practice slowly familiar with the good, but the top-down data learning approach allows you to have a better foundation and a more global vision of the data.

Fifth, technology learning first, you have to learn to get data from the database or other sources, many data analysts still rely on IT staff to get data, but the era of big data, it is really necessary to do it yourself, because relying on others is too inefficient, at least you have to know SQL, SQL is basically even a convenient tool for statistical data extraction, graphical perspective is far from being SQL is very expressive, that's the basics.

Secondly, you have to know some data analysis tools, EXCEL is the most basic, in fact, most of the data analysis based on EXCEL to cope with has been more than enough, EXCEL's graphical expression of the ability to have been strong enough.

The above layers of recursion, in fact, every data analyst in IT on the further, bringing the benefits of geometric, for example, you know Hadoop, then, you may be a little closer to the big data.