Benefits of Data Science

 Data science is one of the fields of study that is revolutionizing the business world the most. By translating numerical information into tangible commercial value, through the introduction to Big Data initiatives, its use empowers any company regardless of its category and facilitates the decision-making process by visualizing patterns of numerical behavior, customers and even resources humans.

Data science companies can increase profitability and improve operations efficiency, business performance, and workflows thanks to efficient prediction algorithms. Today, more than half of the world's organizations use it as a knowledge tool to obtain competitive advantages in the market and plan their business strategies. 

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n the world of Data Science we talk about big data, business intelligence, statistics, machine learning and other technical concepts that arise every day with the advancement of technology. Although the tools come with solutions, many people do not go further and perceive them as complex.

Therefore, professionals in this field have a great challenge: that clients do not see this matter as an incomprehensible or distant science, but on the contrary, try to incorporate it into “non-numerical” profiles, to understand and enjoy data analysis . A good implementation of an analytics model should be based on the premise that numbers are not boring.

This may seem like an empty reflection in a group of smart businesses, but in reality, it consists of raising awareness so that companies not only limit themselves to transforming data into information, but also strategies to solve a problem or improve a process.

It is the collection of various knowledge or skills around being able to understand and solve a problem. This science is responsible for collecting information, unifying it and making use of it to solve hypotheses.

This is achieved with statistical support, for example, around the understanding of the user, applying segmentation methodologies such as RFM or machine learning algorithms, which anticipate the future of the behavior that users will have. There are algorithms for every need that is encountered, it is a very academic subject, supported in mathematics and statistics.

There is another component of Systems Engineering to automate processes and ensure that information and results arrive at the moment they are needed and it is not a wear and tear of a work team that grinds and grinds data so that results arrive late, when they are not can take any action on it.

Data Science collects, for example, user research, databases or information found on the internet at Dane sites, the Chamber of Commerce and Supersociedades, among others (in the case of Colombia).

This is a trend, but it is not about delivering the results based on statistics, with relationships or formulas, but rather talking about a reality based on the data and the processing that we give to solve a need.