Learn what data visualization developers do and how to prepare yourself for becoming one in terms of acquiring necessary skills by analyzing their daily responsibilities.
- [Voiceover] Data visualization is also industry neutral. That is, data visualization developer can work in any industries because their skills are applicable to wherever data is being used. For example, there are a lot of research and development organizations out there including companies specializing in visualization seeking new innovative ways to visualize data. Media companies such as news outlets are also hiring visualization developers.
They need infographics to draw attention from their readers and viewers. Of course any data analytics groups in industry and academia would like to hire their own data visualization developers. Although working independently at times, data visualization developers are expected to frequently work with various teams of people dealing with different aspects of data science. For instance there will be working very closely with data scientists, business intelligence architects, machine learning specialists, and business analytics specialists on a daily basis.
Their primary job is to work collaboratively to identify the most appealing and effective means to visually express data mining and analytics results to help develop new insight and to assist in making critical business decisions. Since it is a development position, this job requires programming skills especially in the area of web development and other Graphical User Interface platforms.
Also a visualization specialist must have knowledge in various database systems and query languages because part of their job is to interface with the database APIs to pull the data before it gets displayed. Finally, they need to be provisioned with mainstream data visualization software tools so that they can speed up their development. After hearing about what it takes to be a data visualization developer, are you interested in pursuing this career path? I believe this job is for you if you're a creative and artistic kind.
Jungwoo Ryoo is a professor of information science and technology at Penn State. Here he reviews the history of data science and analytics, explores which markets are using big data the most, and reveals the five main skills areas: data mining, machine learning, natural language processing (NLP), statistics, and visualization. This leads to a discussion of the five biggest career opportunities, the four leading industry-recognized certifications available, and the most exciting emerging technologies. Along the way, Jungwoo discusses the importance of ethics and professional development, and provides pointers to online resources for learning more.
- A history of data science
- Why analytics is important
- How data science is used in social media, climate research, and more
- Data science skills
- Data science certifications
- The future of big data