Career in Data: Ultimate Guide for You to Know Everything About This Expanding Profession

Discover everything about a career in data, the possibilities for expansion, and the areas of expertise for professionals within the company.

With increasingly growing demands in the market, the IT sector is always expanding and constantly seeking skilled labor. Of the 15 Emerging Professions in 2020 mapped by LinkedIn in Brazil, nine are directly related to information technology. Among the most prominent areas is the career in data.

The growing demand for professionals in this field is due to the current scenario: we have never collected as much data in human history, and more than that, with technological advancement, we have learned to process this data and transform it into important information, which provides a significant competitive advantage for companies.

We can affirm that currently, data can be considered as assets of a company, and knowing how to handle them correctly enables the resolution of company problems, generating more accurate demands that allow its growth.

Therefore, a career in data will be increasingly in the spotlight. For those who want to advance in this area, know that this is a well-structured sector full of possibilities for different profiles.

Come with us as we tell you everything about a career in data and its variables. Enjoy the reading!

Why Start a Career in Data?

Not too long ago, the data field was called the "job of the future," and it's safe to say that future has arrived! Today, professionals in this sector are already among the most sought-after in information technology.

The good news is that those interested in entering this field find two major advantages: there is little qualified labor, and salary offers are quite attractive. These indices go completely against the current economic scenario of unemployment and low offered salaries. Therefore, investing in a data career can be a very wise choice.

Academic Background in the Data Career

To tell the truth, there isn't a specific required education, but what we can say is that having a facility with numbers and logical thinking is essential for working with data.

Similarly, some knowledge of statistics will help you interpret the data, and knowing algebra can help you translate the volume of data into graphs and tangible representations. Therefore, most of the time, data professionals come from the exact sciences field, but it's not a rule.

The Various Possibilities of the Profession

For professionals interested in the data field, it's essential to understand the various possibilities of action and observe the current market needs, as well as how each company is dealing with these positions internally.

The fact is that a lot has changed, especially due to the COVID-19 pandemic, which further boosted the expansion of careers related to data and artificial intelligence, as many companies were forced to adopt the digital work model.

From this change, many solutions and tools – which were previously exclusively used by large companies – also became important for small and medium-sized enterprises. In this context, many companies and professionals who know how to handle these tools have emerged, further increasing the demand for related careers.

Due to this entire scenario, among the currently expanding roles is the data scientist career. Come with us as we explain everything!

Data Scientist Career

Data Science is one of the broadest areas within the segment. Data scientists seek patterns and information that allow for insights, trend prediction, problem-solving, or even anticipating problems before they occur.

Thus, the data scientist is responsible for collecting, managing, and transforming a large amount of unstructured data into usable models, enabling the extraction of relevant information, crucial for the company's results.

This data can be used for quantitative and qualitative analyses, whether analyzing a consumer group, a specific market niche, a company, or even its employees. In summary, the data scientist transforms a tangle of records into valuable products for the company.

It's worth mentioning that this profession should gain more and more prominence because today everything can be quantified, and companies are increasingly connected to this strategy for business expansion.

As a practical example here, we can mention the continued typing on certain search sites, which auto-complete with each repeated search you make, already suggesting that it knows your profile, and that the search engine knows what you're looking for. A very commonplace context to understand that anything can be captured and transformed into data.

Pointed out by the World Economic Forum's Future of Jobs report for 2020 as the most promising profession for the coming years, the work of a data scientist combines statistics, programming, and a strategic business vision.

Required Knowledge and Skills

Now, let's talk a little about the necessary knowledge for this professional. Come with us!

Data Scientist's Hard Skills:

• Programming Languages (Python, R, Java);
• Database Manipulation (SQL);
• Statistics;
• Predictive Models;
• Machine Learning;
• Data Visualization;
• Software Development;
• Data Visualization Tools (Power BI, Tableau, Google Data Studio, Metabase, etc.).
  

Data Scientist's Soft Skills:

• Critical Thinking;
• Effective Communication;
• Business Sense;
• Negotiation;
• Curiosity.
  

Academic Background

Regarding academic background, as we mentioned a few paragraphs above, there are professionals from all fields because the data scientist career is relatively new. Currently, it's mainly formed by professionals in Engineering, Computer Science, Administration, Statistics, and even Economics.

Since the profession also deals with big data, a large mass of data, to draw good conclusions, it's necessary to know artificial intelligence and business intelligence techniques well.

Now that you know about the Data Scientist career, the profile, and the field of expertise, how about learning a bit about another possibility (among many) that a data career enables you to follow? Let's talk a little about the Data Analyst career. An equally current area and in considerable growth.

Data Analyst Career

"Data is the new oil," the phrase uttered by Clive Humby, a London mathematician, makes complete sense to us now, right?

First of all, it must be said that just obtaining data does not bring results for companies. Data must be treated and compiled by trained professionals; only then do they become safe to be used for business decisions, regardless of the company's size.

This is (also) the role of the Data Analyst: responsible for collecting, compiling, analyzing, and correctly interpreting the obtained information. This analysis aims to guide the company in various areas, assisting in strategic decision-making or contributing to achieving results. It can work, among many areas, in partnership with marketing or sales campaigns, for example.

In addition to knowledge in data compilation, the analyst needs to have a sharp interpretation capacity, as well as knowing very well the area in which they are inserted.

And here we are specifically talking that they must know in-depth about the company's market area because the analyses made by the data professional will be used to assist in important decision-making in the company.

What Are the Differences Between the Two Areas?

As we mentioned above, the training for professionals in both areas is very similar. Familiarity with numbers should also be taken into account, as well as some more technical aspects such as programming languages and statistics. That said, the difference between the two professions lies in data treatment. Come with us as we explain!

Data Analysts examine and explore the data, seeking to identify trends, patterns, and possible errors that are specific to the company. Based on this information, they create presentations, graphs, and reports to help in the decision-making process of the business, answering specific questions posed by the company.

Data Scientists, on the other hand, can do the work of Data Analysts but go further by mastering machine learning and creating new processes for data modeling. They work with algorithms, predictive models, and much more, capable of formulating questions for the data to "answer" and identifying solutions that will likely benefit the company.

Understanding the importance of a career in data for the modern world is crucial. If you enjoyed this content, stay tuned for more tips coming soon. Until then!