The modern world is filled with data in all its areas. Science, economics, ecology, medicine, finance, industry – everything is built around the collection and analysis of a large amount of experience. The accumulation of it helps to identify patterns and make decisions based on this data.
What are data science and data mining?
It is the science of methods for analyzing data and extracting valuable information and knowledge from them.
Data science services are responsible not only for analyzing a large amount of data, but also determine the very approach to processing, sorting, selecting, and searching for a new one.
The main value of analytics is that it is often difficult for the human brain to discern patterns where a machine can easily find them.
With it, you can:
- against thieves;
- calculate fraud with bank cards;
- personalized marketing;
- simulate risks for investment or lending;
- Risk modeling;
- personalize marketing and increase its effectiveness;
- financial projections;
- make financial projections;
- customer segmentation;
- segment customers;
- marketing personalization;
- create recommendation systems for the most relevant offers to clients.
Data Mining does not have a generally accepted Russian-language term, but it is interpreted as extraction or mining of information. They also say “deep analysis” or «mining”.
Its essence is in the search for new interpretations of previously known knowledge necessary for decision-making. A person processes information from a point of view familiar to him and to society, and Data Mining has no framework and stereotypes.
Examples of data science business solutions
– By storing information about a past order, a data science solution can predict what this user will want to buy the next time they visit the site.
The advantage of such systems is that they can store a huge amount of information about all user visits, and draw parallels that are not characteristic of the human brain.
As a result of forecasting, the user makes a purchase faster, and it is in the online store that somehow understood his needs.
In the service sector
– Insurance companies, banks, tour operators, and many other companies use it.
Insurance and banks can use in-depth analysis to assess risks when issuing a loan or life insurance. Tour operators, and other entertainment companies for the purpose of advertising and personalized offers.
As a result of using data science, risks are significantly reduced and resources are saved.
In offline retail
– All cards, questionnaires, polls are large amounts of data that are regularly collected by many chain stores.
But collecting information is not enough, and it is science solutions that can efficiently process it and make accurate predictions about user needs.
As a result of personalized marketing, the buyer through the messenger is encouraged to visit the offline store again.
In the media
– Use to estimate and forecast demand.
To decide which films/programs will be interesting at a certain time, the target audience of a particular channel, or music on the radio. In cinema, the demand for a future film is predicted in order to decide whether the shooting will pay off.
As a result of using data science methods, getting the highest ratings at a lower cost.
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