With the rapid development of society, the rapid popularization of the Internet, data analysts have become the most sought-after in this era, the most popular occupation, so how to become a qualified data analyst? Huilongguan IT training that need to have the following five skills!

One, skillful business skills

Only in the practice area has done data analysis work, will understand that all the analysis of the top priority is business knowledge itself. However, the learning and mastery of business knowledge is the need for a certain amount of time and accumulation of experience, to train a data expert, the need for a long time cycle, far more than the basic skills described below. Data analysts are actually in the 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 speak, you not only want to understand it based on business capabilities, but also to 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 kind of practice, it can make your knowledge more systematic and in-depth, data analysis is used to a certain extent to verify 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, across the process is very long, you need to face the different positions, encountered different roles, the use of different languages, to express your requirements and access to what you need to be the bridge between data and business! It's hard to do that without adequate communication skills.

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 other people's efficiency is too low, at least you have to know the SQL, the SQL even basically for statistical data to get the number of convenient tools, graphical pivoting SQL is basically a handy tool for fetching statistics, and graphical pivot is nowhere near as expressive as SQL, which is basic.

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 graphical expression has been strong enough. The above layers of recursion, in fact, every data analyst in IT on the front step, the benefits are geometric, such as you know Hadoop, then, you may be a little closer to the big data.