How Data Science Helps Business: IT Company Experience

Big data is the ways of collecting, storing, processing, and analyzing information. A collection of data is called a data set, and a specialist who works with it is a data scientist.

Today data science solutions such as services for recommendation and scoring or systems of intelligent apartment selection are popular in a great variety of business sectors: in banking, retail, tourist business, insurance, and many others.

Today data science solutions such as services for recommendation and scoring or systems of intelligent selection are popular in a great variety of business sectors: in banking, retail, tourist business, insurance, and many others. There are some well-known online projects of neural networks generating nonexistent human faces based on a huge number of real photos. Some neural networks also write coherent and meaningful texts.

How Data Science Helps Business: IT Company Experience - mytechmint

How it Works

Data Also Includes Facts

Call center receives more calls during the day than the night. Therefore, there should be less workers at the night shift. But this is not enough to build an accurate model. It is important to take into account the following information:

  • an average number of incoming calls every day during a week, a month and a season. For example, during summer holidays the number will decrease;
  • an information on calls distribution within 24 hours;
  • number of employees, days off, public holidays and leave schedule;
  • caller’s geolocation. It is essential to pay attention to time zones difference as when there is morning in European region, it is night in the USA;
  • other information, such as call center specialists’ salary, lunch breaks, five-minutes breaks and so on.

An artificial intelligence algorithm will not only build the optimal work schedule for operators, but will also take into account all data changes and will constantly optimize it according to them.

Science is Data Analysis and Processing

How Data Science Helps Business - mytechmint

How Does it Assist Business?

Netflix, YouTube, Amazon and other services are already using “smart” recommendation systems. Netflix is analyzing users behavior and suggests an individual content according to their past preferences. YouTube creates personalized recommendations for users based on views, likes, dislikes, and other options. Google shows targeted ads based on what sites has a user visited and what he or she has bought. Target, the American trading network, analyzes the history of purchases and changes in customers behavior, then sends them individual discount coupons, as if predicting their desires. In other words, there are plenty successful examples of artificial intelligence algorithms use in business.

Data Science and Myths

Myth #1. Computer Algorithms are Uncontrollable

In fact, the programs created by a human work only within the specified framework, and analytics specialists train them. Therefore, their behavior is predictable, and the final decision is always after a person.

Myth #2. Algorithms Capacity is not Suitable for Business Tasks

Myth #3. Big Data and Machine Approach are Expensive

In fact, working with data will reduce other expenses, for example, on business analytics. In addition, a system works 24 hours a day and expenses can be paid off within approximately three or four months, depending on the features of the project.

Myth #4. Artificial Intelligence will Completely Replace Human Beings

In fact, AI cannot do without people: it needs them to learn a new data. Eventually it is people who construct hypotheses and process the results of AI work. Some professions will disappear, but there will be new ones associating machine learning.

Myth #5. No Data for Processing

Big Data and Business

  1. The consumer receives not a useless advertisement, but a really valuable information. It results in high motivation and increasing loyalty to a brand.
  2. A conversion grows.
  3. Businesses reduce costs and increase profits through more efficient warehouse management, balance monitoring, and accurate procurement planning.

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