The data area continues to be increasingly
Posted: Sun Jan 19, 2025 6:03 am
sought after in the market, both in Brazil and worldwide. Companies in all segments require a data team, after all, the proper interpretation of data can bring many benefits to the business, such as cost reduction, increased efficiency, competitive advantage, identification of opportunities, among many others.
Therefore, if you intend to work in this area, it is very important to understand more about this career, starting with the distinction between the professions of data analyst and data scientist. Do you know what each one does?
Don't worry. We've created this special content so you can learn more about these two professions that are in high demand in the market. We'll explain what each one does, what training is required, and details about the careers of these professionals. Keep reading and get your questions answered!
What does a data analyst do?
A data analyst is a professional responsible for collecting, organizing and interpreting statistical data . They must master specific data analysis tools to reach conclusions and provide relevant insights for the business, which will help in decision-making.
In general, we can say that the data analyst is the first step in a car how famous is botim of worldwide eer in this area . This is because they do not yet need to have in-depth knowledge like a data scientist must have.
However, to be considered a competent professional, you need to perform your role in such a way as to structure the data according to the patterns found. This requires a certain level of knowledge and, with it, generate valuable insights.
It is also worth mentioning that this is a generalist role . In other words, the data analyst is a versatile professional who can work in different teams and roles.
And what does the data scientist do?
A data scientist is a professional responsible for analyzing and interpreting raw data using Big Data and Machine Learning algorithms . In this sense, the work of a data scientist can be compared to that of a data analyst. The difference is that the former uses more advanced algorithms and has more solid knowledge in the area of statistics.
The role of a data scientist is not merely technical. It goes beyond that, assuming a strategic role in companies, capable of generating a high impact on the organization. After all, with their knowledge, they can predict future patterns based on previous patterns.
This allows relevant mappings and experiments to be carried out so that the company can grow sustainably and based on solid data. Particularly in the technology area, the data scientist deals with infrastructure, machine learning, testing, among other sectors.
What are the main differences between a data analyst and a data scientist?
As you may have noticed, both data analysts and data scientists have similar roles, but with different levels of complexity and different ways of working with data.
Below, check out the main differences in the role of data analysts and data scientists.
Data Analyst
The data analyst:
explores and searches for patterns, trends and possible errors in the data, gathering insights;
uses analytical techniques and prepares regular reports for the company;
creates graphs and tables to make visible what the data shows;
analyzes data from sources such as CRM, Data Warehouse, Data Lake and relational database, however, it usually works with one source at a time;
seeks solutions to questions previously formulated by the company;
An analyst is not expected to have experience with machine learning or the ability to build statistical models.
Data Scientist
The Data Scientist:
is an expert in data interpretation;
has qualifications in programming and machine learning;
is capable of creating new data modeling processes;
works with predictive models and algorithms;
presents business vision, with the ability to convert analysts' insights into a business story (Data Storytelling);
explores and analyzes data from multiple sources at the same time;
has knowledge of SQL language;
formulates the questions for which certain solutions can benefit the business.
What are the technical skills of a data analyst?
The data analyst must have some essential technical knowledge and skills for his/her work routine. Check it out!
Programming languages
Data analysts need to have knowledge of programming languages such as Python , R, and SQL . These are important for them to be able to manipulate data appropriately, as well as create visual representations and perform statistical analyses.
Visualization tools
The analyst must master tools such as Tableau and Power BI . They are widely used to create visual representations of complex data.
After all, it’s not just about creating simple graphs. These tools allow the analyst to tell real visual stories with the data collected.
Therefore, if you intend to work in this area, it is very important to understand more about this career, starting with the distinction between the professions of data analyst and data scientist. Do you know what each one does?
Don't worry. We've created this special content so you can learn more about these two professions that are in high demand in the market. We'll explain what each one does, what training is required, and details about the careers of these professionals. Keep reading and get your questions answered!
What does a data analyst do?
A data analyst is a professional responsible for collecting, organizing and interpreting statistical data . They must master specific data analysis tools to reach conclusions and provide relevant insights for the business, which will help in decision-making.
In general, we can say that the data analyst is the first step in a car how famous is botim of worldwide eer in this area . This is because they do not yet need to have in-depth knowledge like a data scientist must have.
However, to be considered a competent professional, you need to perform your role in such a way as to structure the data according to the patterns found. This requires a certain level of knowledge and, with it, generate valuable insights.
It is also worth mentioning that this is a generalist role . In other words, the data analyst is a versatile professional who can work in different teams and roles.
And what does the data scientist do?
A data scientist is a professional responsible for analyzing and interpreting raw data using Big Data and Machine Learning algorithms . In this sense, the work of a data scientist can be compared to that of a data analyst. The difference is that the former uses more advanced algorithms and has more solid knowledge in the area of statistics.
The role of a data scientist is not merely technical. It goes beyond that, assuming a strategic role in companies, capable of generating a high impact on the organization. After all, with their knowledge, they can predict future patterns based on previous patterns.
This allows relevant mappings and experiments to be carried out so that the company can grow sustainably and based on solid data. Particularly in the technology area, the data scientist deals with infrastructure, machine learning, testing, among other sectors.
What are the main differences between a data analyst and a data scientist?
As you may have noticed, both data analysts and data scientists have similar roles, but with different levels of complexity and different ways of working with data.
Below, check out the main differences in the role of data analysts and data scientists.
Data Analyst
The data analyst:
explores and searches for patterns, trends and possible errors in the data, gathering insights;
uses analytical techniques and prepares regular reports for the company;
creates graphs and tables to make visible what the data shows;
analyzes data from sources such as CRM, Data Warehouse, Data Lake and relational database, however, it usually works with one source at a time;
seeks solutions to questions previously formulated by the company;
An analyst is not expected to have experience with machine learning or the ability to build statistical models.
Data Scientist
The Data Scientist:
is an expert in data interpretation;
has qualifications in programming and machine learning;
is capable of creating new data modeling processes;
works with predictive models and algorithms;
presents business vision, with the ability to convert analysts' insights into a business story (Data Storytelling);
explores and analyzes data from multiple sources at the same time;
has knowledge of SQL language;
formulates the questions for which certain solutions can benefit the business.
What are the technical skills of a data analyst?
The data analyst must have some essential technical knowledge and skills for his/her work routine. Check it out!
Programming languages
Data analysts need to have knowledge of programming languages such as Python , R, and SQL . These are important for them to be able to manipulate data appropriately, as well as create visual representations and perform statistical analyses.
Visualization tools
The analyst must master tools such as Tableau and Power BI . They are widely used to create visual representations of complex data.
After all, it’s not just about creating simple graphs. These tools allow the analyst to tell real visual stories with the data collected.