Have you thought of importance of communication skills in data analytics / data science jobs? Yes analytical and problem solving skill is importance but communication is also equally important to make the end result proper. Digging through a huge pile of raw data, organizing and manipulating them and garnering insights from them will seem to be a meaningless exercise, if we are not able to communicate our findings in a comprehensive and unambiguous manner to the stakeholders, management, professionals from other departments, customers etc., The goal of a data analyst / data scientist is to collect and organize data, derive insights and communicate the findings to help the management make informed business decisions by unveiling the power of data. To achieve this, a data analyst / data scientist needs to have good verbal and written communication skills. They also need to be proficient in various visualization tools to convey their insights with analytical and storytelling ability to non-technical professionals such as customers, management, professionals etc.
Why do 80% of the analytics projects fail to deliver business outcomes despite the best insight, accurate predictions & powerful algorithms? It is not due to data or technology, BUT, due to inadequate presentation skills to articulate your findings, due to which you are not able to garner much impact for your outcome. You can build trust and loyalty with your end users or stakeholders only if you are able to create maximum impact on your findings.
Communication skills is the key to any Data Analyst / Data Scientist roles be it oral or written communication, where you will be relied upon to communicate your approaches and findings to non-technical professionals, senior management, or customers etc., It is therefore essential to develop a good communication skill so that your analysis / reports are understood by one and all. In other words, you will have to garner insights from complex data and translate them into clear recommendations that your stakeholders can understand and act upon them after understanding their implications while making informed decisions. You should be able to clearly explain how you arrived at a specific conclusion, rationally justify your approach, and how the findings will help to improve your overall business.
To become an effective data analyst / data scientist, you will need to have a clear understanding of the business practices, goals and objectives, emergence of new techniques and technology, workflow etc., and how their findings will impact the company as a whole. These findings can be used for various purposes, such as optimizing operations, driving innovations, improving customer experience etc., It is your ability to articulate effectively, that will enable the management to understand the implications and take appropriate actions.
Here are some tips to communicate effectively in Data Analytics and Data Science positions:
- Hone your Presentation Skills: Presenting your findings is a vital part of a data analyst / data scientist job, enabling the management and other stakeholders to understand your perspective. Over-complication and excessive use of jargon will only complicate matters.
- Use a structured communication strategy (Storytelling): For sharing insights, a good analytical and storytelling skill can help. For that follow these three steps, you will have to Frame the Story – i.e.., set the context to understand the relevance of the story, Convey the Story – i.e. use interesting narrative to get your story across, and Summarize – reiterate the moral of the story towards the end.
- Data Visualizations: it helps individuals interpret the data visually enabling them to quickly absorb insights and drive decision making process. Graphs and charts really help in this scenario. As you know, data is abundantly available, and we need to understand how to tame it in order to get a clear picture of the data. It order to convey the findings from data, we need adopt various analytical and presentation skills so as to report the trends and make projections.
- Collaboration : To become an effective Data Analyst / Data Scientist, you will need to work alongside other professionals and stakeholders viz., Data Engineer, customers, Marketing & Sales, etc., which includes both internal and external stakeholders, and share your findings.
- Make your audience feel connected and engaged. You must be able to convey your message clearly to all stakeholders. While making presentations, do not read directly from the slides and cheat sheets, because the slides are only a prop. You the person should be the main focus throughout. Talk and engage with your audience. For eg., Always ask questions to the audience before proposing the solution viz., have you developed such models before? Or What tool did you use for Data Visualization etc
- 6. Listen Patiently: Be a good listener. People are happy if they are being heard instead of formulating a quick response.
- Be Formal while communicating officially : Do not use informal language during a formal conversation with your superiors and during the meetings. Avoid typo mistakes while sending formal mails.
- Body Language : Maintain your body language during face to face meetings and video conferences. Maintain eye contact so that the other person knows you are paying attention.
- Maintain a positive attitude.
- Always be brief and to the point. Display analytics and other representations only in few numbers only say maximum slides. You will have to describe your representations briefly and to the point.
- Think properly before you speak. Communication skills is not only how effectively you speak but also what you speak. Always try to communicate the right audience and the right content to get best possible result.
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Hence, the successful data scientist will comprise both technical and non-technical skills. Remember, a career in data science promises to be a highly rewarding, well paid, provide excellent learning opportunities, opportunity for growth etc. Effective communication is a fundamental skill for those working on data and to be proficient in Data Analytics / Data Science, you will need to be an effective communicator. The data scientists may have the best insights, but what matters more is the outcome.
Having a right attitude along with the thirst to acquire knowledge and development of soft skills can go a long way, and will help you to achieve your goals and succeed in the field.