A importância das habilidades interpessoais na análise de dados

Technology   |   Jason Belland   |   May 15, 2023 TIME TO READ: 3 MINS
TIME TO READ: 3 MINS

What’s your image of the typical data scientist? Male? Young? Works in isolation? It’s time to challenge this stereotype.

In 2023, data analytics is an increasingly diverse and accessible profession. A recent U.S. survey revealed that 49.8 percent of data analysts are women. And while it’s far from perfect, the wage differential between men and women is much narrower than in other tech professions. In 2021, women earned 95% of men’s salaries and that gap is closing rapidly.

The rise of low code and no code in data analytics

Another myth is that you need a background in coding and databases to apply for a data analyst role. Yes, you’ll probably need some technical knowledge, but employers are increasingly likely to offer training for entry level roles. We’ve also seen an increase in the number of ‘low-code’ or ‘no-code’ data analytics tools. Modern interfaces enable non-technologists to contribute without resorting to Python, SQL and other programming languages.

In the meantime, hiring organizations are putting greater emphasis on the soft skills that enable data analysts to flourish. Interpersonal skills are a good place to start. Communicating effectively enables data analysts to understand the needs of team members, clients, and stakeholders.

Creativity and innovation also score highly. Analysts must be able to think outside of the box to find new ways of approaching problems and finding solutions that bring value. This requires them to explore different approaches, identify trends, and come up with creative solutions that help drive successful outcomes.

Attention to detail is essential. Data analysts must be able to pay attention even when dealing with large datasets or complex algorithms, as small mistakes can lead to incorrect conclusions or results. In addition, they must have an eye for accuracy and precision when it comes to writing code or interpreting data.

Flexibility is another important trait. If you enjoy working on ‘straight line’ projects that flow uninterrupted from start to finish, data analytics may not be for you. Data analysts often work on multiple projects operating within tight deadlines. You should also be comfortable working with a range of tools and technologies and be able to adapt them to the project at hand.

You must also be resourceful.  A good data analyst isn’t afraid to hack together different tools, platforms, and datasets to solve a problem. You’ll need to go beyond your comfort zone to solve complex problems or interpret results correctly. It also means you’ll need understanding of wider business goals and strategies to source relevant information from internal sources such as financial statements or customer feedback surveys.

Last, but not least, critical thinking skills are essential. Data analysts must be able to develop creative solutions to problems, analyze and interpret large amounts of data, and make decisions based on logical reasoning.

Furthermore, you need to have the ability to explain complex concepts in simple terms so that your colleagues can understand the results and implications of your analysis. Ultimately, it is these critical thinking and communication skills that allow data analysts to become valuable assets for any organization looking to leverage the power of data-driven decision making.

In the next article we’ll look more closely at the types of businesses accelerating their hiring plans for data analysts including medicine, retail, financial services, and sports.

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