What soft skills should a business look for in a data analytics professional?

Every sector of the economy is increasingly adopting the data economy. Numerous businesses have gained a distinct competitive advantage through the use of data, and data-driven businesses have demonstrated improved business performance. As a result, a lot of businesses are looking for skilled data analytics professionals who can help them get insights for measuring in order to grow their businesses.

So, what are the skills that a professional in data analytics should have? The majority of current discussions regarding data analytics skills Centre on techniques or business, programming, mathematics, and statistics knowledge. Hard skills like these can be measured, quantified, and quickly learned through training. Even though these hard skills are important, a person's personality, interpersonal skills, and work ethics are also important for a data analytics professional. Habits and characteristics that influence how a person works and interacts with others are referred to as soft skills.“62% say it’s difficult to find those with technical skills and 60% report they have a hard time finding those with the personal attributes they need,” according to a recent global survey of leaders across industries.

However, what soft skills should a business look for in a data analytics professional? Although the requirements for soft skills vary from company to company, there are some universal ones that are applicable to almost every data analytics position in every business. Communication, collaboration, critical thinking, curiosity, and creativity are the five Cs of data analytics soft skills, many of which are interrelated. Let's examine the specifics of these five Cs, as well as methods for developing them.

1.Communication It is essential to have effective communication skills if you want to quickly and accurately comprehend information for yourself and others. In a data analytics project, communication includes listening in addition to writing and speaking. One must be able to listen carefully to others, particularly data and insight consumers, in order to comprehend their insight requirements and decision needs. Customers of data and insight may be ambiguous in expressing their requirements due to the complexities of business and technical issues. Engaging in active listening and asking pertinent, probing inquiries aids in defining and defining their actual requirements and needs. As a result, business stakeholders like data and insight consumers can open up to data analytics professionals, avoid misunderstandings, and build trust.

2.Collaboration Data analytics requires collaboration between business, IT, and data teams. The professional in data analytics can successfully collaborate with other teams to achieve the common objective. The following characteristics can be infused into collaboration to further enhance it: respect for other team members, their opinions, and the willingness to inquire about their thoughts and opinions on a variety of topics are all examples of open-mindedness.

3. Critical thinking: ?The capacity to think rationally and logically and to solve problems in a consistent and methodical manner is known as critical thinking. Data analytics is fundamentally about gathering information that can be used to answer questions and make decisions. In data analytics, critical thinking skills include deriving and communicating actionable insights, evaluating the ethical aspects of using insights for decision making, identifying biases associated with framing the questions, validating the assumptions, selecting the appropriate models, and critiquing the accuracy of the analysis and results.

4. Curiosity: ?In data analytics, being curious is a crucial soft skill. This is because projects involving data analytics are fraught with a variety of obstacles, including unclear decision objectives, time and resource constraints, a lack of expertise, low-quality data, and ethical and privacy concerns. The fields of business and data analytics are always changing, and professionals in analytics can always learn new things, improve their skills, and broaden their knowledge. In data analytics projects, curiosity also improves a person's ability to quickly overcome obstacles by asking powerful, open-ended questions that open up possibilities and encourage deeper comprehension and discovery.

5.Creativity A good analytics professional will always try to come up with new insights that are current, accurate, and relevant to the business. Being creative enables analytics professionals to consider and investigate divergent possibilities and perspectives prior to settling on a specific analytics solution because there will frequently be multiple approaches to addressing the requirements and needs of users. Experimentation, or determining the variables' causal relationship, is closely related to it. In general, data analytics experimentation and creativity are vehicles for business innovation.

To become successful data analytics professional, hard or technical skills are essential. However, data analytics professionals need to have strong soft skills in addition to their hard skills in order to truly deliver maximum business value. These soft skills include communication, collaboration, critical thinking, curiosity, and creativity. Although it is commonly believed that you need hard skills to land a job in data analytics, it is your soft skills—particularly the five Cs—that will ultimately help you advance and achieve success as a data analytics professional.

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