Updated May 2, 2023
Introduction to Careers in Data Visualization
Data Visualization is defined as the pictorial representation of the data to provide fact-based analysis for decision-makers, as text data might not be able to reveal the pattern or trends needed to recognize data. It involves the need for Bachelors’s/Masters’s degree in Computer Science or data visualization postgraduate degree, So; by doing this, anyone can get the role of Data Visualization Engineer, Business Intelligence Analyst, or Data Analyst in organizations, and their average annual salary based upon the American website would be between 60000 – 100000 dollars.
Education to Know the Careers in Data Visualization
Bachelors / Master’s degree in Computer Science or any other relevant field.
Few junior/graduate visualization analyst roles are advertised – visualization is often a component of specific data analyst or data scientist roles. To pursue your career in one of these fields, you typically need a degree in a subject that develops your analytical skills, such as maths, statistics, and computer science.
If you want to specialize straight away in data visualization, you could consider studying for a data visualization postgraduate degree.
Career Path in Data Visualization
To be a data visualization engineer, one needs a degree from University in a subject that develops analytical skills like Maths, Statistical, and computer science as they must have strong analytical skills.
Let us clearly understand the different career paths and skills required for them.
Categories
There are three broad categories of Careers in Data Visualization:
- Data Visualization Engineer: The data visualization engineer focuses on designing and developing reporting solutions to provide fact-based analysis to the decision-makers to identify patterns and trends that text data may not reveal. The Data Visualization Engineer position requires a Bachelor’s or Master’s degree.
- Business Intelligence Analysts: Business Intelligence Analysts focus on data analysis and business reporting. Analyze business requirements and develop functional specifications. Business Intelligence Analyst is responsible for building reports, dashboards, models, and tools to analyze data, report, and present operations-related data, which is used to monitor product usage, to make important business decisions, and forecast business productivity. Sometimes they also need to engage with internal and external clients to determine requirements, decide on priorities of requirements & make sure that there is no communication gap.
- Data Analysts: Data analysts work on reporting and visualization to explain the hidden figures of data with the help of graphs, charts, etc. Their role is to analyze data collected from sales, marketing, etc., and help the firm make better decision-making by presenting their finding in the form of reports. A bachelor’s degree is required for the Data Analyst position at the entry-level. There are different categories of data analyst positions: operational analyst, marketing analyst, financial analyst, etc.
Job Positions or Application Areas
Many types of data science problems lead to different skill sets for each issue. Thus there are other roles in this field:
1. Data Visualization Engineers: To be a data visualization engineer, one needs a degree from University in a subject that develops analytical skills like Maths, Statistical, and computer science as they must have strong analytical skills.
Following are some skills that one must have to have a career in data visualization. Data Visualization engineers must have good coding knowledge of languages such as Angular.js, d3.js, Python, etc.
- Skill Set: Strong analytical engineer, Excellent communication skills (both written and verbal), Attention to detail, and Excellent math and statistical skills. Programming Knowledge with Angular.js, d3.js, Python, ability to query relational databases & big data platforms (NoSQL systems), HTML & CSS knowledge, etc.
- Application Areas: Aerospace, Information Technology, Banking, etc.
2. Business Intelligence Analysts: Business Intelligence Analyst needs to have good written and verbal communication skill; they should also have experience in data analysis, and they should have coding knowledge in statistical packages like R, Python, MATLAB, & SAS for data analysis.
- Skill Set: Good coding knowledge of Java, Python, Scala, etc.
- Application Areas: Aerospace, Healthcare, Retail Sector, Banking, Transportation
3. Data Analysts: A data analyst position requires excellent programming knowledge and communication skills. Analytical skills to work with data and find conclusions are also needed. Data Analysts present their findings as an understandable document; thus, good communication (speaking and writing) is necessary.
- Skill Set: Communication, MS Office suite (Excel, MS Word, PowerPoint) Knowledge, SQL Skills.
- Application Areas: Consulting, Healthcare, Banking, Procurement.
Salary (US Data and Not India-Specific Figures)
As per the information from Indeed.com:
- Business Intelligence Analyst: The average salary for a Business Intelligence Analyst is around $90,000 USD.
- Data Engineers: The average salary for data engineers is around $100,000 USD.
- Data Analyst: Depending upon the experience level, the average salary of a Data Analyst may vary from $60,000 to $90,000 USD.
Conclusion or Career Outlook
Data Visualization Engineer is essential since the average human brain process visuals 60,000 times faster than text. Today data visualization is used in almost every industry. The need for a Data Visualization engineer is also increasing as data is increasing day by day, so it is becoming difficult to understand it and make a decision on it unless it is presented in a more meaning-full or understandable way; so pursuing a career in Data Visualization is a really good decision. Suppose you are planning to explore careers in data visualization. In that case, you should consider pursuing a degree in Data Visualization related fields & focus on developing analytical skills, such as maths, statistics, and computer science.
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