Blog of the Data Science for the Digital Society research group. Digital Society Innovation, Applied Artificial Intelligence, data analysis and smart living and business.

21 June 2022 | Posted by angela.tuduri

What Data Science is and how to become an expert

Our environment is increasingly complex. The ecosystem in which we operate today is very different as compared to years ago, which did not use or analyze the data of the digital environment. We currently live in a world full of information translated into data, also known as big data.    

What does it all mean? In today's post we share with you the meaning of data science, the attributes and skills you will need to become an expert, as well as the most sought-after career opportunities in the market. 

What is Data science   

Data science is the technique used to analyze, understand and study information of any kind. It is a discipline which allows the examination of large amounts of data and obtain significant conclusions for the business or organization.    

Today, through statistics, computer science and programming, advanced information management has made it possible to significantly improve a company's chances of success. Today's digital economy, based on process automation, big data and the internet, is here to stay.    

This means that companies' previously unknown structured data sets (big data) can now be understood and prevented from negatively affecting the business. We are in a digital era, which, combined with artificial intelligence, machine learning and ICT, makes it possible to investigate data from any field: medicine-health, social sciences, education... among others.    

Types of data    

There are different types of data to analyze. Today we will show you the most common ones used by professionals in the sector:    

  • Open data - is the data that anyone can access. This data indicates the external characteristics of a business. It is information without restrictions and free for everyone.    

  • Smart data - smart data is data of business value. This information can be translated into useful and necessary data for business purposes.    

  • Identity data - as the name suggests this data contains individual user information including address, name and purchase history. By analyzing this data, we can interpret the behavior of our users. 

Reasons why we use data science    

Data science helps us recognize points of improvement or hot spots in a business. Data experts or data engineers seek to establish patterns of interest to users and thus offer them what they like the most.   

Their main objective is to know the trends and the public's reaction.  

These patterns will influence the company's decision making and will be key in the choice of strategies and product or service improvements. In addition, data science uses mathematical resources, probability models and machine learning to help optimize subsequent analysis. 

Therefore, why is data science important? 

Importance of data science 

In a world as digitized as the one we live in today; it is becoming more and more complex to retrieve information from the Internet. There are thousands of data to analyze in the different digital channels.   

Every movement made by a user will be recorded and can be analyzed later. All the information is recorded in what is known as a data center. A data center is the storage place where the computers that store all the company's information are stored.  

The importance of data science is growing every day. As new technologies advance, large volumes of data allow us to understand the behavior of our users. Today, the data analyst plays an important role in the business environment, as he or she oversees interpreting the information stored in big data.   

What does a data scientist do? 

A data analyst or data scientist is a professional who, through programming, computer science and mathematics, analyzes the data collected and draws conclusions and patterns that improve the experience and quality of users. 

The skills and characteristics required for such a profile revolve around data extraction and cleaning, as well as processing and structuring data to draw conclusions for improvement.  

Skills  

The most outstanding skills of a data scientist are: 

  • Mathematics - mathematical knowledge is very important to prepare your analyst profile. Understanding the information held in the data will require calculus and algebra skills for the professional.  

  • Statistics - In addition to understanding mathematics, statistics are a must have in data analysis to understand and structure data.    

  • Programming language - In addition to Java and C++, a data engineer will need to understand the basics of programming language such as SQL (structured query language) and master programming with R and Python that will allow you to clean and extract all the data and information.    

  • Visualization - the last step is to analyze and understand the data collected. Knowing the tools that help you visualize the data to expose it will be essential in your analyst profile. 

Roles in demand  

More and more companies are demanding an analyst profile. The increasing digitalization leaves us with huge amounts of data that in turn store valuable information about users and consumers. The advancement of technologies also favors profiles of this type.    

Data science has been considered as the job of the future, being one of the main assets for business. A study published by Deloitte confirms that the irruption of technology has positioned data scientists as a priority in hiring.    

The most sought-after jobs related to data science are:    

  • Data engineer  

  • Data architect   

  • Data analyst   

  • Analytics consultant   

  • Data modeler 

How to become a data scientist 

If you are thinking of becoming a data scientist, here are some specific courses that prepare you for it. At La Salle Campus Barcelona you will find the necessary studies to become a data analysis professional.   

The Master's Degree in Data Science will teach you to analyze and project large amounts of data, to develop in the field of the Internet of things, smart cities, digital business... If you prefer, you can take the master's degree online and remotely, adapting the contents to be 100% flexible. If you prefer to specialize in big data and learn to design and develop scalable ICT infrastructures, the Master in Big Data of La Salle URL teaches you the necessary techniques to become a professional.   

If you want to understand the basics of data analytics in Barcelona, discover our Campus courses and start shaping your future! 

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