How to Become a Data Visualization Engineer?

Companies can no longer work on only Excel sheets to manage their data. Today, we generate such a massive amount of data, commonly known as big data, that traditional database management systems fail to handle and process it. As such, companies need advanced tools and techniques to gain meaningful insights from customer data. Professionals like data scientist and data analysts are capable of using such tools. After the data is gathered, pre-processed, and then analyzed, it is crucial to visualize it so as to find patterns easily and communicate the results to the stakeholders and other business leaders. 

Data visualization isn’t a new term in any way. You too must have created some bar graphs or charts when learning math in high school. Representing data in the form of graphs, charts, or maps is nothing but data visualization. Why the term has now gained so much importance is due to the growing adoption of big data analytics to make informed data-driven decisions. You will find many powerful data visualization tools in the market designed to fulfill the soaring demand for better data visualization capabilities. It has created a competitive field for companies that offer data visualization tools, the key players in the market being Tableau, QlikView, Power BI, and Google Charts. 

So, it definitely makes sense to learn data visualization and open your doors to many data-related jobs available out there. Those looking for gaining expertise in different data visualization tools can take online courses, like Tableau eLearning, and begin to gain foundational knowledge.

Who is a Data Visualization Engineer?

Simply put, a data visualization engineer is someone who is responsible for representing data in such a way that identifying correlations and trends becomes quite easy and the same can be communicated to the stakeholders to draw meaningful insights. Such professionals usually gather a complete overview of the business processes and the problems that an organization is facing. They try to solve these problems by acquiring the company data and use advanced tools and techniques to find hidden patterns that go unnoticed by business leaders.    

As the companies continue to leverage the power of big data and business analytics, the demand for data visualization engineers is expected to grow significantly in the near future. Now, you are wrong if you think that data visualization engineers are required only in the Information Technology sector. Their demand is also seen in finance and banking, eCommerce, advertising, healthcare, and government agencies.  

Some of the major responsibilities of a data visualization engineer include:

• Convert text data into interactive visualizations by conducting fact-based analysis and highlighting the patterns observed.
• Work on machine learning algorithms that involves the model designing and testing
• Gather data from different sources and convert them into a single format so as to conduct proper analysis and visualization. 
• Understand the data at hand and determine which tools and presentation ways would best represent the trends and patterns. It is because not every kind of data can be visualized best through a specific tool or chart type. 
• Customize tools as required and deliver visualizations that are easy to support and sustain by a support team.

Becoming a Data Visualization Engineer  

The world of data visualization today has gone far beyond the usual bar graphs and pie charts. As data visualization engineers are being hired in varied industries, different employers may look for different skills that would suit their projects. However, here are some common steps that will prove your readiness to take up a data visualization engineer position. 

• Gain a complete overview of the broad fields like big data, data science, machine learning, statistics, and more. Learning its basics comes handy when visualizing data.
• Gain data acquisition skills and data preprocessing skills as the data may not always be ready for creating visualizations. 
• If your project involves collecting data from databases, it is highly recommended to know how to write SQL queries. 
• Learn storytelling, i.e., how to communicate the story represented through the identified trends so that even non-technical people can understand it.
• Become well-versed in using data visualization tools like Tableau, QlikView or Power BI.
• Master programming languages like R or Python as they are helpful not only in data visualization, but also in data analytics, statistics, and data mining.

Bottom Line

We hope you now have a clear understanding of what it takes to become a successful data visualization engineer. Now, if you are similar to most of the people who can’t follow these steps on their own, then better take up an online course to master these skills. You’ll get highly-skilled professionals as your mentor who know what employers actually look for while hiring data visualization engineers. What’s more! You will get access to powerful tools like Tableau which would otherwise require you to pay a hefty amount for access. So, without further ado, start learning data visualization today and witness a rewarding career ahead.