We are in an era where data has become the most valuable resource for organizations.

Due to technological innovation and the advancement in the digitalization of businesses and society in general, the volume of data generated daily has increased considerably. Therefore, data professional profiles are crucial in the current context.

In fact, according to forecasts by the European Commission, 75% of European companies will have implemented Big Data processes by 2030, and there will be a significant increase in their investment.

But merely collecting data does not yield optimal results; it is necessary to make the most of it. This factor has led to an increased demand for data professionals, experts in data science, who can manage large volumes of data and unify all the information, as it can be obtained from various sources or be in different locations: in the cloud, on-premise, structured or unstructured.

These profiles help to derive learnings, make predictions, optimize decision-making, and efficiently boost business activities. Proof of this is that the data analyst profile was the second most demanded profession last year according to Randstad’s annual report.

But what skills does a Big Data professional need today?

Firstly, to manage various databases and conduct in-depth analysis, it is important to have training in different areas such as:

• Programming Languages. SQL is one of the main languages for managing and downloading information from a database and is thus essential to know. It allows querying the common databases in Big Data environments. Moreover, languages like Python or Scala offer the tools to analyze data stored in DataLakes, making them indispensable as well.
• Apache Spark and Apache Flink, are two open-source projects for distributed data processing, being the most used tools.
• Data Mining. Identifying patterns to improve business operations is one of the benefits of having training in data mining.
• Artificial Intelligence and Machine Learning. The emergence of AI and generative tools like ChatGPT should alert these data professionals, who need to stay up-to-date with the latest industry trends.
• Quantitative Analysis. As mentioned earlier, collecting data is only part of the functions of a Big Data expert. The ability to analyze will enable them to identify patterns and trends within the vast amount of information they handle.

However, it’s important not to focus solely on technical knowledge. In an era where speed and communication are vital, so-called soft skills are equally important for this type of profile:

1. Analytical Thinking: Breaking down the task into simpler parts allows evaluating different situations and getting a view of the problem from various angles for resolution. Analytical thinking will help the Big Data professional manage and analyze information efficiently, as well as identify patterns and relationships between data to find new business opportunities.
2. Effective Communication: Experts in this sector work with many departments and business areas, so it’s essential they can clearly and concisely communicate their ideas and findings to other members for a much more effective and productive process.
3. Teamwork: As mentioned before, this professional works with numerous departments for information analysis, so it is necessary to have certain social skills that allow them to manage teamwork so that each project member knows their role and how their performance contributes to a common goal.
4. Creativity: For data visualization, this soft skill is a crucial factor as it involves developing new ways to communicate this information to users, from a simpler point of view, so that users who are not proficient in data analysis can understand this valuable information. Moreover, results are often reflected visually with graphs and interactive maps for the entire organization to understand the data’s value. To complement this soft skill, it is advisable to handle tools like Seaborn, Plotly, or Folium.

Challenges for Data Professionals

The Big Data sector is rapidly evolving, and many companies already have hybrid infrastructures (cloud and on-premise) to handle large data sets. More qualified and specialized data professionals are increasingly needed for these roles based on cloud management software such as Cloudera, Google Cloud, AWS, Azure, and Oracle.

At PUE, we believe that the future of the Big Data expert is continuous learning and certification, key factors for any organization to achieve success. Check out our training courses and become a data professional!