Data Science

The task of a specialist is a thorough processing of data sets and obtaining a predictable result. The result of the research is a model, which is an algorithm for further actions in solving the problem. A model is a model that is an algorithm for further actions in solving the task.

Basic principles

Data science is based on mathematics. The methods of linear algebra, statistics, optimization are mainly used to work with data. Data science is based on mathematics.

The procedure of Data science consists of 5 main stages:

1. Data collection. The purpose of the collection, the required amount of data, and the methods by which the information will be obtained are determined.
2. Preparation. Formation of an up-to-date database and its validation.
3. Processing. Separation of information and determination of the methods that will be used in the work for a specific task.
4. Analysis. Processing of the data science project – analysis and forecasting based on the data obtained. A data science project is created for each specific study. It necessarily includes several stages: hypothesis, experiment plan, assessment of the suitability of the results for solving a specific task.
5. Communication. Presentation of data in the form of reports, on the basis of which proposals for solving a specific task are made.

Any project has a chance for error or exception.

Sphere of application

Data science is actively applied in commercial and non-commercial organizations as well as for private use. The discipline is most often used in the following:

• Demand forecasting. Based on past sales data, future demand can be forecasted. Regularities are determined, which allow you to quickly plan and restructure business processes.
• Recommendations. Internet services use Data science to generate suggestions based on user preferences, such as music, videos, online shopping, etc.
• Pricing. Internet shopping companies have data on sales of the previous period. This information allows you to analyze the prices and form the best offer.

The volume of data is growing regularly. In this regard, Data science technologies are also rapidly developing, providing great opportunities for obtaining and processing data in various areas. Data science technologies are also rapidly developing, providing great opportunities for obtaining and processing data in various fields.