Careers in Data Visualization

 

Careers in Data Visualization

Data Visualization is defined as the pictorial representation of the data to provide the 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 of Bachelors /Masters 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 a Data Analysts in organizations and there 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 more often a component of certain 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:

1. 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. Bachelor’s or Master’s degree is required for the Data Visualization Engineer position.
2. Business Intelligence Analysts: Business Intelligence Analysts focuses on data analysis and business reporting. Analyze business requirement 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, take important business decisions and forecast business productivity. Sometimes they also need to engage with the internal and external client to determine requirements, decide priorities of requirement & make sure that there is no communication gap.
3. Data Analysts: Data analysts work on reporting and visualization part 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 position: operational analyst, marketing analyst, financial analyst etc.

Job Positions or Application Areas

There are many different types of data science problems that lead to different skill sets for each problem. Thus there are different 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 in order to have careers in data visualization. Data Visualization engineers need to have good coding knowledge with languages such as Angular.js, d3.js, Python etc.

• Skill Set: Strong analytical engineer, Excellent communication skills (both written and verbal), Attention to detail, Excellent math, statistical skills. Programming Knowledge with Angular.js, d3.js, Python, ability to query relational database & big data platform (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, they should have coding knowledge in statistical packages like R, Python, MATLAB, & SAS for data analysis.

• Skill Set: Good coding knowledge with languages such as Java, Python, Scala etc.
• Application Areas: Aerospace, Healthcare, Retail Sector, Banking, Transportation

3. Data Analysts: Good excel programming knowledge and communication skills are required for a data analyst position. Analytical skills to work with data and find conclusions are also required. Data Analysts present their findings in the form of an understandable document; thus, good communication (speaking and writing) skills are a must.

• 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 important since the normal 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 careers in Data Visualization is a really good decision. If you are planning to explore careers in data visualization, 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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