Data Science is the discipline that is responsible for converting data into useful knowledge. Data Science masters and works the data life cycle from beginning to end. That is, not only does it stay in the part of storing data or in the process of ordering it, but it works in the life cycle of the data in a complete way to the point that the data is exploited for a specific purpose.
It is the grouping and ordering of data from different sources so that it can then be edited in more understandable ways. This is in order to tell a ‘story with the data so that it can be understood by all and of benefit for certain objectives
How Data Science works
Data Science works from Big Data; that is, on a large volume of data. The point of having this large amount of data is because you want to use it to answer various questions that can help the business.
However, this valuable information cannot be extracted if it is not possible to sort out all the chaos of data that exists in the databases beforehand. Big data is sorted through Data Science. That’s one of the benefits of Data Science. To do this, data scientists must be in charge of asking the right ‘questions’ to receive the specific information they want to get.
These ‘questions’ are determined from the tools that Data Science uses.
Tools used by Data Science
• Programming
To apply Data Science in a company, it is necessary to use programming in order to explain to computers what is needed from them. In this way, it is possible to reduce a very complex task to a series of steps that can be solved with code languages interpreted by a computer.
• Statistics and Mathematics
Analytical skills are required to deal with situations of uncertainty, which are constantly present when performing data analysis.
Therefore, statistics and mathematics are important to extract insights from data more accurately and sophisticatedly.
• Domain knowledge
This Data Science tool consists of accumulated experience in a particular sector or field such as physics, medicine, parenting, etc. In this way, it will be possible to know the questions that should be asked to achieve an expected answer.
The importance of Data Science
The importance of Data Science is that it allows us to understand what happens, why it happens, what will happen in the future, and how we can make a result happen in the future.
Therefore, the benefit of Data Science is powerful, as it helps companies to order their strategy and forces them to make decisions based on the data that exists. Consequently, actions are carried out with which there is a better visualization of the expected result.
Data Science analysis
• Descriptive analysis
It allows businesses to understandably summarize what happens in real-time, as well as facilitates the delivery of reports on actions carried out by the business. For example, with the use of Data Science in marketing, you can answer questions about how many visitors a website obtained in the last month or how many sales have been made this week.
There is even the possibility of knowing how dollar prices vary around the world in real-time. The value of Data Science in this analysis is above all to inform and provide data that points to performing strategies and actions with greater security.
• Diagnostic analysis
Here Data Science seeks to investigate the reasons behind a phenomenon. You don’t just want to know the information or data, but the reasons why it happens.
An example of Data Science under this diagnostic analysis is as follows. A coffee chain wants to invest in a new location, so it plans to use Data Science to make sure its investment is the best.
With this objective in mind, it is not only necessary to know the places most used by the public to which I want to sell, but also to know why those places are usually full. With the use of Data Science, it will be possible to know that information and make sure that the reason that there is a large audience is that the prices of the stores in that place are really low.
This information would be valuable if the coffee shops in this chain are characterized by low prices. On the other hand, if the price strategy is high, the investment would be bad.
• Predictive analytics
Using Data Science with predictive analytics is used to predict specific outcomes. For example, knowing what your clients will do this week or what sales will be achieved for the first two weeks.
The importance of Data Science for this type of analysis is that it evaluates different strategies to achieve specific objectives. That is, the same technology offers different paths that the company can take regarding a need and presents them with the prediction of the results that each path would generate.
Application of Data Science in companies
The application of data science is diverse. Not only does it cover a sector or certain areas of an organization, but it can be used for marketing, psychology, human resources, economics, biomedical science, and many more. Some of the applications of Data Science in companies include:
• Product recommendation systems
Product recommendation systems are very common in e-commerce. It helps encourage the users to buy multiple products. Therefore, it helps a lot in conversion within the customer life cycle.
For this, Data Science is used to extract information from search engines and social networks. This is in order to collect data on browsing history, purchases, tastes and preferences, and sociodemographic information of the public of interest.
All this information allows training machine learning models in order to make more precise recommendations based on the profile of different users.
• Weather forecast
This type of solution is very useful for agriculture, as it can forecast weather and natural disasters with great precision. To achieve this success, information is collected from satellites, radars, airplanes, and ships to build models capable of predicting meteorological information with what is Data Science.
This is how the application of Data Science allows people to take the appropriate measures at the right time, prepare for weather changes and avoid the maximum possible damage.
• Tumor detection and treatment search
In the field of medicine, Data Science is of great help, since it offers the ability to identify diseases. There is even research that affirms that this recognition system is better than the human specialists themselves.
To perform this task, a large amount of information and research is required to statistically train the computer. In addition, Data Science and Artificial Intelligence must work hand in hand for a more effective image recognition system to be produced.
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