Data science as a profession is arguably the hottest career of the 21st century. In our current dispensation of advanced technology, everyone has pressing questions that must be answered by "big data". From non- profit organizations to businesses to government institutions, there is a large amount of information that can be analyzed, interpreted and applied for diverse purposes. 

Finding the right answers can, however, be a difficult nut to crack. How can a non-profit organization further enhance its potential operations with their available marketing project? How can government departments create engaging community activities using behavioural patterns? How can industries and companies sort through purchasing dossier to create a market strategy? It all comes down to data scientists. 

Thus, the question, what is data science and who are data scientists?

Datalogy refers to a multi-disciplinary field that uses scientific means or patterns, algorithms, processes and systems to extract information from structured and unstructured input. This field employs the use of abstract analysis, statistics, machine learning and other related methods in the understanding and explanation of actual phenomena with the abstract. Often called data mining and big data, it uses theories and techniques drawn from different fields within the context of computer science, statistics, mathematics and information science.

On the other hand,  data analytics specialists are professionals trained to spool, analyze and organize abstracts and figures, helping industries, companies and institutions make sense of information gathered from audios, videos, social media, comments, e.t.c. Data mining is a  very complex and confusing field that requires different skills, some inherent, while others can be learned. 

This article thus highlights some of the non-technical and technical skills expected from an individual aspiring to study data science or is already in the process of becoming a data scientist.


Curious Nature

Albert Einstein once said "I have no special talent. I am only passionately curious." It's no surprise this quote comes up anytime data scientists are mentioned. This field requires individuals with a constant drive to get answers or solution irrespective of the amount of raw info that is being thrown at them. It's a field that is evolving very fast, so you can't rely on prior knowledge. It requires constant learning, so you must have the desire to read more, know more, analyze things and also get answers.

Organized Personality Trait

Big data requires a keen ability for proper organization. As pointed out earlier, there are millions of potential dossier points, so keeping each one at a particular place and finding more solutions and in general, making sure your information is organized in a useful way is essential. Excellent organizational ability will help you reach the perfect conclusions at the end of your work.

Positive Stubbornness

Findings have revealed that this career path can be very frustrating at times, so a great deal of determination is a good thing. When things get very tough, and it seems like there is no answer forthcoming, a good data scientist will keep reanalyzing and reorganizing and if need be get more info with the hope that a new perspective will present itself that will lead to a victory song "Yes! Yes! Yes! I got it."   


One of the jobs of data analysts or data mining specialist is predictive analytics, that is, anticipating future demands and events, and also recommending cost-effective alterations to procedures and strategies. This can be possible only with a creative mind. One needs to have a creative, innovative and inventive mindset before going into this career to acquire more knowledge and skill set.

Attention to Details

Aspirants of this profession need to have acute care to details. This line of work involves the analysis, interpretation and organization of large amounts of unstructured info.  Every equation, every picture, every alphabet, every number e.t.c, is very vital in the process of data analysis.

Communication skills

An excellent data mining specialist should be able to fluently and clearly translate analytical and technical findings to a non-technical department. Having good communication skill gives you an edge when going into this profession. A data analytical analyst must be able to relate well with business development and marketing teams to ascertain their needs, analyze the available abstracts and profer solutions.  


A data analytical specialist cannot work alone. You have to work with designers and product managers to manufacture better products, work with marketers to launch better advertising and converting campaigns, work with server software developers to create and improve workflow. You will literally work with everyone in that industry or organization, including customers.


Most of the technical skills required to becoming a data scientist can be acquired via knowledge, learning and training. These technical skills set includes the following:

1)  Fluency and experience in many of these computer and coding programs: SPSS, PYTHON, SAS, MATLAB R, C/C++, JAVA, PLATFORM, SQL/NoSQL Databases

2)  Expert technical skills in

  • Statistics

  • Machine learning tools and techniques,

  • Data cleaning and munging,

  • Data visualization and reporting techniques

  • Mathematics ( calculus, linear algebra and probability)

  • Unstructured data techniques e.t.c

In conclusion, you don't need to have all these skills(primarily Non-technical ) before going into the field of data science, but having them positions you to have an added advantage in your pursuit.


Published by Charlesa Gibson