5 Key Traits of a Data Artist That Every Data Scientist Needs

5 Key Traits of a Data Artist That Every Data Scientist Needs

We are living in an era where over quintillion (1 followed by 18 zeros) bytes of world data is being generated every day by our digital interactions such as daily commuting, online shopping or social networking.

In the past decade, Big Data solutions have become the most impactful breakthrough in the data science industry. There has never been a better time to pursue a data career to help organizations wade through the Big Data challenge: to achieve value-add business analysis and unlock data insights to meet their business goals.

Data Scientists have been widely recognized as professional data wizards. Harvard Business Review named the title of Data Scientist as “the sexiest job of the 21st century”. The job is “sexy” because Data Scientists need to work at the intersection of computer science, machine learning, data mining, statistics and analytics to help a business gain competitive advantages. This skill set is extremely valuable, but very rare in almost any workforce.

The rise of Data Artists: Who are they?

Several years ago after the “analytics luminary”, Jim Sterne, introduced the concept of the Data Artist in his article, “From Data Scientist to Data Artist”; Data Artists seem to have stolen the bright halo from Data Scientists and have become the new emerging data wizards. Sterne defined his concept as:

A Data Artist is responsible for delivering fresh insights from data to help an organization meet its goals. This is the person who takes the output from decision-support systems and turns it into consumable theories, postulates and hypotheses that can be tested and applied to the business...

At a glance, Data Artists seem to do part of the job that Data Scientists always do. Both Data Scientists and Data Artists share the same goal: take some real-world data, explore it to create connection and pattern and show the insights in some creative way.

However, their practices are affected by their cultural differences.  Data Artists not only create insights, they also create beauty to evoke people's emotion.

What are the key skills for a Data Artist?

Data - As painters must know pigments and engravers must know rocks, Data Artists must understand characteristics of data. Data is the Data Artist’s raw material. Every data set has its own specification, strength and limitations. Data Artists need to be familiar with different data that can go into their artwork and know the best way to use the observations from data to vitalize a piece.

Engineering - Data Artists should be able to use their baseline understanding of engineering to discover data correlations, conduct data analysis, develop metrics, decide what metrics to be used for visualization and how to show data patterns and trends to their audiences.

Art - Just as a painter use brushes, Data Artists should be able to use analytics and visualization techniques to transform large streams of data into meaningful, creative and beautiful business insights. There is no set formula for good works of art, but there are some elements they have in common: they are beautiful to look at, easy to understand and are inspirational.

Communication - One of the most valuable skills a Data Artist has is the ability to help people communicate quickly with visual thinking. Data Artists help people move away from dry numbers and make them more engaged in the information. They deliver clear messages using visualizations. A message itself could be a conclusion or something to direct people to draw their own conclusions.

Business - Being a successful Data Artist is not only about creating great art, but also about understanding the business goals. Data Artists need to understand business goals to promote and maximize the value of the information.

Why should we care about Data Artists?

Data visualization is not always realms of statistical graphing or intricate dashboards. The growing trend is combining aesthetics and data science approaches to drive people to particular insights, to speak to their emotions and to keep them attracted.

Introducing the concept of the Data Artist does not necessarily mean replacing the Data Scientist.  Rather it means to inspire Data Scientists. Adding art to scientific studies can encourage Data Scientists to consider different ways to convey their data analysis results or ideas to audiences, particularly to non-technical audiences.

In many data sectors (especially in today’s digital marketing sector) the new preference for information discovery has included art elements that require data analytics experts to adapt. The growing appeal of visual beauty has provided Data Artists even more opportunities to fascinate, engage and create perspective for their audiences. The art form of data visualization is still young, but it is increasingly becoming popular because Data Artists can help people see or perceive the same world in different ways.

Article written by Jason Li
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