5 Soft Skills the Data Analyst & Scientist Needs for Success

Developing people skills is the new frontier of success for the data professional to realize the promise of data making an impact and transforming the enterprise.

The real world of working with data in the enterprise reveals some significant gaps in the toolkit of the data professional. While the environment is replete with technical competence, tools and programming knowledge, all of these capabilities lend themselves well to human to machine interfaces, i.e. people working with systems. What can be lacking is the set of skills in working with people. Machines don’t have emotions, entrenched views, or biases (unless programmed that way). A solid technical skillset is no longer enough. The well-rounded data professional needs a set of soft skills in order to be successful in the dawning era of the modern data-driven enterprise. This article considers five such soft skills that would make an impact in the toolkit of the data professional.

Soft Skill 1: Change Awareness

There are such foundational skills needed in life that leaves one wondering why we are not taught them in school growing up. Like how to negotiate or deal with conflict. Learning those skills as a kid would certainly make it easier to navigate life’s challenges. Well, in much the same vein, change awareness is a skill that every data professional should learn prior to starting their career. Remember the promise of data? It is supposed to transform the organization. Well, if that is true and that is what is taught in schools and universities, when is it that data professionals are not equipped to at least be aware that data can impact change and that change needs to be managed. It doesn’t mean the individual needs to manage the change, but they do need to be aware that it is a possibility.

Soft Skill 2: User Experience

User experience, the feelings a user experiences when interacting with an interface, is a well understood and valuable field in the software industry. Yet is has not yet made the same splash in data and analytics world yet. That is gradually changing. However, the data professional can still stand out from the crowd by learning from the field of user experience.

Even a basic knowledge and application of user experience principles can be a game changer for the data professional and most of it is common sense such as leveraging personas when gathering requirements. Personas also offer a great way to push back on chart junk and low value information.

Soft Skill 3: Wireframing

One of the most impactful skills the data professional can learn is how to wireframe. This pertains to those who must present data to end users either through a report or dashboard. Why is it so impactful? The practicality of it. Wireframing brings so many things together. It can build consensus, gain alignment, drive towards business value and save buckets of cash. Don’t bother building that dashboard until you have sign off on the wireframes, it’s going to save so much time. Even better, wireframe in PowerPoint, no need to learn a new tool. Just collaborate with stakeholders until the wireframes are in a good state. We have a free PowerPoint Wireframe template we can give away.

Soft Skill 4: Data Storytelling

Storytelling with data is a widely used term but is not necessarily easy to execute upon. The data analyst that understands the narrative arc will be able to capture the attention of the audience and bring them on a journey that leads to action. Storytelling is foundational skill that every data professional should have. An extension of storytelling is data visualization best practices for without one you cannot achieve the other. Knowing what the data-to-ink ratio is as well as appropriate chart selection to picking the right layout for the dashboard are all vital to drive adoption.

Soft Skill 5: Facilitation Skills

One of the hardest soft skills to master is facilitation. Especially for the more introverted professional. Yet, bringing people together in a room to align of leveraging data and building consensus yields huge dividends. So many big rocks can be addressed early that can save us major heartache later on. Often what happens is that, in order to avoid friction, difficult topics are put on the long finger and only come to the fore later in the development process. Without these being addressed in smaller chunks, they can come together in a more intense manner and even potentially derail the data project. While this is a big ticket skill, it is not without danger and risk as bringing a group of professionals together into one room, where there might be existing tensions, can blow up on the inexperienced facilitator.

Conclusion

With technology progressing as fast as ever and more and more people choosing data as a career, it is important that we don’t forget the people skills that will enable success and allow a smooth path for data to fully realize the promise of bring able to transform organizations.