In our previous post, we shared the top technical skills for starting a career in Data Analytics. While having the right set of technical skills is crucial, there are other non-technical yet equally important competencies that help you stand out as a distinguished analyst.
At Paragon Shift, we always stress the importance of our team members' soft skills in addition to their data manipulation skills. We will share with you the main four skills that make a successful data analyst.
#1 - Business Acumen
Business acumen is the sense of understanding the business's planning, operations, strategy, and finance and how they are all integrated.
A data analyst with high business acumen knows not only how to visualize the data but also what business questions need to be answered by the data. The analyst understands the industry trends and patterns and knows how to solve current problems, avoid future mistakes, and support growth.
#2 - Communication and Story-telling
One of the main responsibilities of a data analyst is to communicate their findings to business users and stakeholders. The analyst should know how to present the information in an easy-to-understand and compelling narrative to tell the 'story' of the data in a manner that promotes the right decision-making.
For example, an analyst going into the details of the functions and operations behind preparing the data would lose the interest of non-technical stakeholders.
Also, data analysts often collaborate with data scientists, data engineers, and other professionals in the field and should be able to relay information to them to ensure a smooth flow of activities.
"If you don't know how to ask the right question, you discover nothing" - W Edward Deming
#3 - Attention to Detail
It comes as no surprise that data analysts need to make sure that there are no redundancies or inconsistencies in the information that they are presenting. If the analyst presents inaccurate information to stakeholders, it will lead to erroneous decision-making that will be costly for the organization.
When working with large and complex data, it is important that an analyst be meticulous and attentive to details to minimize human error.
#4 - Research
Data analysts interact with huge amounts of data in different ways, and we cannot expect that they have all the information they need at their fingertips. Often, they work with unfamiliar industries or are inexperienced with particular business processes or tools.
In those cases, analysts need to be adept at researching to have a better understanding of the context of their work. Moreover, the world of data is constantly changing and new solutions always unravel. Data analysts also need to do constant research to keep up with the latest technologies.
It is not all set in stone
You may have realized that you already have one - or more- of the skills mentioned in this post. If that's the case, then good for you! However, if you are not, do not worry, with enough practice, you can fine-tune and enhance any of those skills until they become natural to you.