My Takeaways from the VizChitra "Breaking into the VIz Biz" Panel Discussion

Tips and suggestions for breaking into and succeeding in the Data Visualization field, drawn from the VizChitra panel discussion:

  • Leverage Your Existing Skills - Panelists noted that many people stumble into data visualization from diverse backgrounds like visual design, consulting, science, and journalism. The skills acquired in these fields, such as visual design principles, data-driven communication from consulting, making complex ideas accessible from science communication, and applying new skills like data analysis from journalism, are highly transferable and valuable in data visualization.

    • "I don't think anyone chooses data viz, data viz happens to them".
    • "My journey started as a visual designer... and at some point I realized that there's so much of information that is out there that there's got to be a better way to present this information".

  • Prioritize and Develop Soft Skills like Curiosity (especially continuous curiosity), the ability to view work as a problem to be solved, strong communication, and presentation skills are highlighted as critical. This includes selling your ideas and persuasion. These soft skills are considered undervalued and harder to teach than many technical skills. Mastering storytelling is also essential for making data understandable and impactful.

    • "Storytelling is incredibly important...to be able to decipher the difference between a good story and a bad story".

  • Understand the Business of Data Visualization - Whether freelancing or starting a studio, success relies heavily on being good at business, which is distinct from being good at making visualizations. Challenges include learning how to reach out, pitch, and price your services effectively. It's noted that data visualization is an industry with "very high need but very low demand," meaning you often have to sell clients on the need itself. Building a team can enable taking on larger projects and balancing execution with business development.

    • "A lot of creatives start a studio because they're good at something. But to start a studio you really don't need to be good at that thing, you need to be good at business which are two absolutely different things".

  • Understand the Technology/Medium (Code Included) While technical tools and coding might be considered easy to learn compared to soft skills, understanding the technology that delivers your design is crucial. Going "one level deeper" than standard graphical user interface (GUI) tools, potentially through learning code (like D3), can enable more creative and experimental visualizations. However, collaboration with developers is also a valid strategy.

    • "Ultimately the technology is the delivery vehicle, and you must know what are the limitations".
    • "For me code is just another way to do things... How can I take my idea out and represent it is more important".
    • Future: General execution – AI, Specialized execution – You

  • Focus on Outcome and Personal Practice - Instead of getting bogged down in discussing the design process, focus on the ultimate outcome and demonstrating the effectiveness of your work. View your work as a personal "sadhana" - practice to improve your skills, regardless of external validation. Be present when working and strive to do your best.

  • Maintain Enthusiasm and Find What Re-energises You - When facing demanding or less creatively fulfilling work, it's important to figure out how to find time for things you're passionate about. Developing an "SOS kit" – identifying activities that help you feel energetic and motivated when you're down – is a self-discovery process essential for navigating the ups and downs of any career.

  • Engage with the Community Joining and participating in data visualization communities, such as VizChitra, can provide a space to "nerd out," discuss challenges, job opportunities, the future of the field, and share work. This engagement can also lead to networking opportunities and spreading awareness about data visualization. Supporting community events through tickets, sponsorships, or volunteering is also encouraged.

    • "The idea is to really give everybody a space to come and nerd out, geek out about data viz, talk about challenges, talk about job opportunities, talk about what the future of data viz looks like".

  • Champion Data Visualization in Corporate Settings - To integrate data visualization within companies, find an "anchor" – someone who understands and believes in its potential. Showing the value through projects is crucial, often starting with "easy early wins" or "low hanging fruits". Focus on how data visualization can help the business or solve problems, rather than just aesthetics. Frame it as a complementary skill to data analysts and scientists, helping to simplify complex data for broader understanding.

    • "The biggest differentiator is if you are actually coming across as someone who is trying to help the business".
    • "It is a complimentary skill - it's not them versus us".
Other comments:

"Teaching is about building a ladder of abstraction for people to climb"

"Elearning was earlier Edtech...Usability was learnability" 

The speakers were Ipsa Jain, Sandeep Karmarkar, Gurman Bhatia, Amit Kapoor and the discussion was moderated by Aman Bhargava

Comments

Post a Comment

Popular posts from this blog

Kai-Fu Lee on China-US AI Race - Q&A Transcript from a Bloomberg Interview

Image
Kai-Fu Lee, Chairman of Sinovation Ventures and author of  AI Superpowers and  AI 2041: Ten Visions for Our Future on the China-US AI Race Q: There's still a lot of challenges when it comes to the whole monetization of AI, according to his perspective. In the last three years, though, how have you looked at this whole evolution of China AI versus the US, and what are the advantages and challenges for China? A: Yeah, so firstly, I disagree on the prospects for the USA. USA because yes, you look at OpenAI, it's making half billion spending 40 billion. It looks like a bad balance sheet, but most of that 40 billion is spent for future revenues. And if you believe there are 2x, 3x, 5x growth for the next three years, it's going to justify that valuation at some point. The bubble is merely that it's gotten ahead of itself, not the likelihood of growth in the future. Not saying it's worth its price, right, but there's absolute substance under the thumb. Now back to t...
Read more

The Mercurial Grok AI Assistant Understands & Speaks Indian Languages

Image
Grok , the AI model developed by Elon Musk's xAI, can understand when you type Indian languages like Hindi, Telugu, Odia or other Indian regional languages using English letters (like when you type 'namaste' instead of 'नमस्ते'), and it can respond by mixing English with those languages. Grok doesn't necessarily need the native script of these languages. It has natural language processing abilities that extend to multiple languages. This is great innovation because many people in India, especially in online communication, use transliteration. Grok can generate responses that combine English words and phrases with words and phrases from the regional language you used in your input. For example, if you ask a question using a mix of English and Telugu transliteration, Grok might respond with a sentence that includes both English and Telugu words. Check these Hindi, Telugu, Odiya samples - Grok, ab Hindi mein Grōk, ippuḍu telugulō Grok, Oḍiā re This way Grok is more...
Read more

40 Talks from the Google Web AI Summit 2025

Image
Front-end leaders share their experience on pushing the boundaries of Web AI and run machine learning models entirely client side in the browser via JavaScript to get privacy, lower costs, and lower latency. From traditional AI models to Generative AI such as large language models (LLMs) and diffusion models, discover the latest advances of Web AI in 2024 that are accelerated by technologies such as WebAssembly, WebGPU, and WebNN.
Read more