Basic Requirements for The Data Analyst Specialty

Data Analyst

Data analytics enables a company to organize and structure large amounts of data, extract patterns and patterns in information, and make the most appropriate decisions to improve productivity.

Data analysis involves processing information through programming languages: SQL, Python, and others. In addition, data consulting services by Dataart specialize in process automation, systematization of complex systems and algorithm management.

Data analyst helps the company:

• Find effective solutions based on the findings.

• Improve the efficiency of production processes.

• Find opportunities for business growth.

• Introduce innovations for further development.

The result of the analyst’s work is the answers to pressing questions, predicting further events in the market, and identifying relevant recommendations that lead to increased sales. Also, the specialist’s duties include software security testing service.

Basic knowledge of data analytics

To accomplish the assigned tasks, the analyst must have certain skills and knowledge in various areas:

• Have a bachelor’s degree in mathematics, algebra, or physics.

• To navigate mathematical theories, statistics, information data.

• Be able to work with hypotheses and validate data.

• Know at least one programming language and be able to use modern platforms.

• Have commercial acumen and understand business processes.

The analyst must be objective about the tasks and be able to work with large amounts of information. Even experienced professionals can make mistakes, so the analyst must be able to track their mistakes and take responsibility for making important decisions.

Job hierarchy data analyst

Like any profession, analytics has its own levels, specializations, and areas of responsibility. Analytics is a difficult industry to understand, and not every “techie” is capable of becoming a good analyst. In any case, in order to get a responsible job, a specialist must go through initial positions and gain the necessary experience.

1. Trainee analyst. The very first stage of a beginner specialist. The most significant criteria by which an intern is hired are the availability of the necessary knowledge and mathematical abilities.

At first, the trainee takes up a lot of the manager’s time, since he does not have experience. As the trainee progresses, they can independently connect to various projects and perform more complex tasks.

2. Junior specialist (junior). The second level of the analyst vacancy presupposes the ability to work with all known data processing tools. The analyst should not be able to program at the production programming level, but the specialist should know the basics of building code and managing algorithms.

As a rule, the junior is not yet able to compile an analytical report, but it is quite possible to entrust him with certain parts of the work on grouping files, tables or frameworks.

Data Analyst

3. Middle analyst. This is the initial level of independent work. A specialist can be entrusted with small projects and simple tasks. At this stage, the analyst must independently cope with the task, which has a clear and logical way of solving it.

An analyst can carry out complex projects as part of a team of employees under the guidance of an experienced leader.

4. Senior Specialist (Senior). The senior analyst should be able to solve problematic issues that do not have a straightforward solution. He serves as an example for the entire team when performing complex projects and all participants in the workflow listen to his opinion.

The senior specialist has significant experience and knows how to use all available tools for working with large amounts of data. As a rule, the senior specialist has the authority to involve junior employees in the execution of the assigned tasks.

5. Leading specialist. This is a professional expert-level specialization. Many years of experience and a strong portfolio allow the leading specialist to set priorities and select employees for himself.

The level of the head of the analytics department assumes excellent knowledge of the business and all the features of the company from the inside. DataArt knows about that some more. The main difference between a managerial position is a higher level of responsibility for the final result of the work of the entire department.