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An analyst is a specialist who processes data and draws up forecasts, strategies, plans, and recommendations to clients based on them.
There are several professions, the name of which also contains the word “analyst” – financial analysts, software analysts, system analysts. All of them are engaged in the analysis of this or that information, but they do not necessarily use mathematics, statistics, and programming languages in their activities. They need to be distinguished from the separate profession of “data analyst” in a data science consulting firm.
A data analyst should be well versed in mathematics, statistics, computer science, computer science, business, and economics.
The data that the analyst processes depends on the field of activity in which he is engaged. For example, an advertising analyst determines the target audience for advertising campaigns: he creates an algorithm that searches databases for information about potential customers, analyzes advertising strategies in terms of response, and evaluates campaign performance indicators.
What qualities are needed to successfully work as an analyst
The qualities are:
- Love for silence and loneliness. Much of the analyst’s job is to interact with the computer, not people. An analyst, if he is not the head of a department, has little contact even with colleagues, let alone clients. He does not hold meetings, his working day is spent at the monitor processing data. There are people who definitely need communication – this kind of work will not suit them!
- Developed logical and mathematical intelligence. It is important that a person likes to operate with statistical data, draw up graphs and tables, see patterns, structure information, highlight the main thing, and discard the secondary.
- Patience. An analyst is not a creative profession. Every day, an analyst has to do the same thing: collecting, analyzing, evaluating data. This work is very similar to the main hobby of my childhood – collecting puzzles. It gave me pleasure to take a set of incomprehensible disparate parts and spend hours collecting from them something holistic, reasonable, and meaningful. Analysts do the same.
- Precision and meticulousness. The analyst mostly deals with the exact categories: data, numbers, algorithms. When making requests, you need to make as few mistakes as possible and select the audience as accurately as possible.
- Mindfulness. The analyst must take into account all the factors that can affect the result of the analysis, do not miss a single important detail, otherwise, at the output, he will receive incorrect data and draw erroneous conclusions.
Data analyst in the future
Modern business is largely based on the analysis of data about customers, sales, the effectiveness of advertising strategies, so the profession of an analyst is now in great demand and will remain so in the coming decades. Promising areas:
- Working with big data;
- Data modeling;
- Economic forecasting.
In addition, the ability to work with a large amount of information (analyze, structure it, draw conclusions) is in demand not only in economics and finance but in any other field of activity.
