Top Skills Beyond the Technical in Data Analytics

Analytics job soft skills

Whilst the qualifications and technical experience required of Data Analytics professionals is somewhat conclusive, those soft skills employers screen for remain undervalued by professionals. Soft skills are becoming increasingly esteemed for those working in the field as the importance of understanding and utilising data in becoming more widely adopted by all departments in a company. After all, it is a Data Analyst’s soft skills that ensure the entire organisation is gleaning the benefits brought by data.

Below are the top five skills that Data Analysts need to succeed.

  1. Attention to Detail

The ability to effectively and accurately interpret data is an unsurprising requirement. Many elements of working within a Data Analytics role is akin to searching for a needle in a haystack. When data sets are increasingly large, it is the analyst's patience and attention to detail that aids to uncover those small clues.

  1. Communication Skills

Whilst uncovering the clues is the first step, without the communication skills to translate the information found in the raw data to the wider organisation, a Data Analyst’s work is pointless. Above average communication is a non-negotiable skill listed in nearly half of all data job descriptions, particularly for roles in Data Science. Part of this communication also involves translating data-driven terminology into a language understandable by the wider organization. After all, data only holds value when it is digestible to all audiences.

  1. Problem Solving

One of the most rewarding aspects of working within Data Analytics is extracting information and solutions that have been overlooked by others. Troubleshooting solutions to extract this information and solving any hiccups the arise along the way is a daily occurrence in the industry. A passion to solve problems is a non-negotiable in Data Analytics.

  1. Creativity

Whilst many would not align a role in Data Analytics with one requiring creativity, but when given large data sets a creative approach to problem solving is invaluable. Exploring creative approaches to tackling data and continually implementing fresh approaches is what helps professionals extract the most valuable information.

Artificial Intelligence, Machine Learning and automated processes are infused with this creative approach. Technological innovation makes adapting to change a continual requirement and gives professionals the ability to take creative approaches further.

  1. Persistence

Finally, and obviously, Data Analysts must have persistence in the face of large data sets and unknown solutions. Persistence is what brings together the need for problem solving, creativity and attention to detail. In data, persevering through the unpredictable obstacles is the key to success.

If your soft skills ticket the above five boxes, chances are a career in the data field will be a perfect pathway. Whether thinking a role in Data Analytics, Data Science or Data Protection, these transferable skills are a must for any professional in analytics.


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