To begin the world of computing and data analysis, we must first know what data science is?
In short, we could define this discipline as the process responsible for transforming data into useful information. Unlike traditional data analysis and processing, data science is responsible for exploring and analyzing data from multiple sources.
Data science is related mainly to Big data due to the number of sources that must be taken into account to perform quantitative or qualitative data analysis.
But what is Big data, and why is it? They are all large files or sources of information that are useful for making decisions on a project. Although they can be in different formats, it is the task of a data scientist to make them understandable and manageable for the end-user.
Why is data science applied in companies?
Without an area focused on data search and processing, companies would be incomplete. Today, organizations that want to stand out from the industry giants must include data science in their processes.
With the help of data science, companies can analyze all the data generated from their customer’s electronic devices when they interact with any of their services. In this way, they can better understand their customer wants and needs to fine-tune their processes.
Today’s companies have social networks, websites, or simply a bank of suppliers. Current and potential customers, not including analyzing, do not represent any value. The important thing is to know how to take advantage of it.
For this, companies need professionals capable of collecting and analyzing qualitative and quantitative data that can be translated into strategies, proposals for improvements, and more
To accomplish that end, and almost like a savior, the data scientist appears.
What is a data scientist?
So, did you notice how important a data scientist is to any company? They all need to have a data scientist. Therefore, the market demand for these professionals has grown dramatically in recent years.
The important thing is that if you want to be one of these sought-after specialists, you must learn from scratch what a data scientist is and what he does. To begin with, a data scientist occupies one of the most significant positions in a company in the digital world.
Ассоrding tо SАS, а соmраny dediсаted tо dаtа trаnsfоrmаtiоn, а dаtа sсientist is а dаtа exрert whо hаs the teсhniсаl skills neсessаry tо sоlve соmрlex рrоblems аnd the сuriоsity tо соntinue exрlоring the diffiсulties thаt mаy аrise аlоng the wаy.
In other words, a data scientist is someone who is trained to perform data processing widely. It can question the information it receives and applies data science in business in all possible ways.
In addition, it is not only limited to developing what is presented to it at the moment. Curiosity and initiative are essential. One of the prominent roles they must fulfill is to explore the environment to analyze possible difficulties and minimize their impact.
In the words of Camila Manera, professor of the Fundamentals of Data Science and Research Data Scientist course at Walt Disney Company:
“A data scientist must have the necessary tools to help him analyze large volumes of data to make smart business decisions. In this way, you will be able to create an effective impact”.
Data scientists, without a doubt, are professionals who come to companies to mark a before and after.
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What does a data scientist do?
A trained data scientist eager to keep learning is what every business wants. But what else is expected of this professional?
If you want to become the next data scientist to transform organizations, you must consider what companies will ask you to do. Thus, you will be able to know if this, indeed, is the profession for you. Coming up next, we tell you:
- Promote data analysis for decision-making.
- Lead the collection and analysis of qualitative and quantitative data.
- Know about data architecture, that is, how a database is formed and everything it comprises.
- Use the best business intelligence and web development tools to process the information you receive.
- Through data processing, you should be able to predict consumer behavior and identify ways to generate income.
As you can see, without a data science expert, companies would have significant limitations when launching their campaigns or managing a project. In particular, if the goal of an organization is to grow or expand, you must consider what it means in data analysis and its importance.
- This is how Camila Manera endorses because for her: “data helps us analyze trends, build correct solutions and expand businesses.”
The best decisions are made with the correct information, so having a data scientist is vital.
The analysis process of a data scientist
Now, you know what is expected of a data scientist and what he should do broadly since these usually vary according to the organization where you work.
However, according to the Barcelona Innovation and Research Laboratory, inLab FIB, the process followed by a specialist or master in data science can be summarized in 5 steps, which we will describe below:
- Extract the data from the primary source that can be webbed, CSV, APIs, and more.
- Clean the data to have a database without errors.
- Process the scientific data obtained using statistics for data science.
- Design a new methodology to process scientific data if necessary.
- Present the results in graphs that are attractive and visually understandable.
While this process does not apply to a junior data scientist, it is what you could pursue if you choose this career in the future. The functions may seem a bit difficult as we’ve mentioned some technical concepts, but don’t worry, it’s all a matter of learning!
Later, we will discuss the courses or programs you must follow to take your first steps in data processing in computing and obtain a job as a data scientist.
Data scientist vs Data analyst
Before focusing on the fundamental studies, you must differentiate between a data scientist and a data analyst. These two professions are often confused; however, they are not the same.
Both analysts and data scientists start from Big data analytics. However, the data analyst is responsible for collecting information, analyzing it, identifying patterns and improving processes.
According to experts on the subject, its role is somewhat limited compared to data scientists. In this way, these professionals are in charge of performing the functions of an analyst and taking them further.
Therefore, if you decide to work as a data scientist, you should know what Big data is for and how to use it. In addition, you must understand how to examine multiple data through advanced analytics tools, always considering a global vision of the problems.
While it may seem more work, there is no doubt that the payoff will be more significant.
What to study to be a data scientist?
Induce that you want to be a data scientist? Cool! You will be part of the transformation of many companies. Above all, you will be able to help them achieve their goals and objectives efficiently.
The paths to becoming a data scientist are many. You can opt for careers in an institute or university in your city, or you can take short courses. What works best for you?
Undergraduate and graduate degrees
Within the long-term options, through the institutes and universities, you can opt for degrees in Applied Data Science, Data Science for Business or other similar ones. The title name will vary depending on your location.
Short courses
If you do not want to start a long-term course, setting up analytics and computing is the best option through short courses.
To get started in this matter, you can opt for the Fundamentals of Data Science and Big data: in the consumer’s mind. Are you ready to challenge your skills and find out if data science is for you?
What programs should you know?
Regardless of the degrees or courses you develop, you must bear in mind that there are not negotiable programs in your training. Next, we will describe what they are to choose and the degrees or courses you should take.
SQL
This programming language will help you analyze qualitative and quantitative data on a large scale. You can handle large amounts of information.
R
Although this programming language is the oldest on the list, it will also allow you to comply with the collection and analysis of qualitative data. Moreover, it has codes and packages that will simplify the tasks.
Python
Data analysis with Python is essential. Most data scientists use this programming language because it is modern and works very well.
Excel
Data analysis in Excel doesn’t regularly use at an advanced level, but it is excellent to start working with your first databases. It will allow you to manage a considerable amount of information and process it.
Challenge your knowledge and dare to transform the digital world by being a data scientist. We are waiting for you in the next post!
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