Data Science

Outsourcing Data Science

Business development requires testing hundreds of hypotheses and interrelated factors. Data Science is the science of data that helps you analyze large amounts of information, extract useful knowledge from it and take action on its basis to improve your business.

Data Science uses machine learning (ML) and Big Data tools – a set of technologies for collecting, storing, processing, analyzing data. A specialist in this field is called a data scientist, and the data sets he works with are Data sets.

We can say that Data Science is a science at the intersection of mathematics, programming, analytics and even linguistics.

How it works

A data scientist develops an algorithm that predicts and models trends, behavior, patterns based on data. The algorithm parameters are determined automatically based on the data.

In simple terms, an algorithm is the calculation of a value using a previously known formula, for example, y = 5x + 2.

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In Data Science, the formula is not known in advance, but is derived from the data obtained. For example, an algorithm can show how a person’s productivity changes during the working day and what factors it depends on.

Data and facts

Let’s say we have a task: to draw up a work schedule for call center operators, which works 24 hours a day.

It is clear that the number of incoming calls at night is several times less than during the day, so fewer employees need to be replaced. However, this is not the only factor that needs to be taken into account. What else will need to be entered into the system:

  • The average number of incoming calls on each of the days of the week, months, seasons.
  • Distribution of calls throughout the day.
  • The number of operators, their vacation schedule, established by law 2 days off per week.
  • The geography of the location of the customers of this technical support service (for example, when it is night in Moscow, in Vladivostok it is day).
  • Other data such as employee salaries.
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Self-learning systems allow not only to mechanically build a graph, but to take into account all data changes and regularly optimize it.

How it can help business

Data science outsource can help directly, and for the benefit of both the seller and the buyer. The simplest and most striking example is targeted advertising in search engines. Google is based not only on queries in the search bar but also on the user’s movements, online communication, activity on social networks, etc.

Many companies successfully use Data Science in their activities.

Netflix, based on the analysis of the behavior of its subscribers, recommends them an individual selection of potentially interesting films and series, and the “cover” of the content is created for each viewer personally.

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YouTube also processes billions of data points every day across millions of parameters and creates personalized recommendations for users.

Target – A chain of American supermarkets sends customers personalized coupons based on their purchase history and behavior analysis.

Even at the state level, there are already proposals to use the neural network in politics and social projects.

Big Data and Business

The examples above show that the simplest thing that Data Science can do is, at a minimum, create personalized recommendations. Even this small amount leads to an increase in profits, because:

1. The client receives useful information, rather than annoying ads, his motivation and loyalty level increase.

2. This increases the chances that the buyer will use the recommendations.

3. The company can more efficiently manage the warehouse, control the balance and plan purchases.

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