Data analyst is an expert in managing, processing, and representing data. His job serves to gain settlements in control, industry, and science. Such specialists usually work in organizations where a data-driven approach is practiced.
He is expected for any project. Collecting and analyzing info is equally relevant for games, education, medicine, and media. Accordingly, wherever it is likely to collect data about the goods plus behavior of the destination public, an analyst is needed.
Data analyst – who is he and what he does
He is a professional who examines data and explains it. That is, the record of his duties involves the number of digital info, their study, visualization, and understanding. The main goal of an interpreter is to profit from the data gathered thanks to data analysis consultancy services.
All analysts are divided into operation analysts and marketing analysts. The latter are narrowly focused experts who monitor individual business processes. For example, an investment, financial analyst or risk specialist.
Policy analysts run in the IT field – these are digital analysts. Scientist is considered one of the current trends. It includes the following professions: Big Analyst, learning, Engineer, Machine learning. Scientist is a specialist who applies special abilities and statistics to resolve dilemmas. This is partly a trend spotter, computer scientist, and mathematician.
How can it be useful for the organization? For example, it is planned to open a cafe. There is data on the cost of rent in different areas, the location of other cafes and public transport. In this case, he can figure out where it would be most beneficial to open a cafe.
One more example. The mobile operator is about to add a new tariff. The scientist receives a database and data on customer behavior from the company, after which he calculates the potential market size and the economy of the new tariff.
The line within operations and marketing analysts is blurred. All analytics systems are required for development, which is achievable within means of industrialization. However, when choosing between these two directions, the digital sphere is more promising. Analytics in Python and additional programming styles make it reasonable to treat large quantities, interpret data faster by automating everyday processes.
Duties and obligations of a data analyst
Analytics is a particular field where operators are expected to hold a specific collection of individual features and experience.
Typically, the operation algorithm of an analyst seems like this:
- Gathering of data. Examining the info system, aims, and policy of the organization.
- Familiarization with the dialing parameters. We are speaking about the kinds and the standards of their sorting.
- Pre-processing of data with structuring and mistake improvement.
- Analysis and resolution of the responsibility.
- Configuration of the result.
Information needed by a operations analyst:
- Way and processing devices, spreadsheets (SQL, DBMS, ETL).
- Programming styles: R, SAS, C ++, Python.
- BI analyst.
- Statistics and math (higher mathematics, mathematical logic, linear algebra, probability theory, etc.).
- Computer and deep knowledge is the capacity to produce or prepare a neural network from injury.
- Data Engineering is an industry of receiving, collecting, and obtaining it.