You're starting a new innovation project. How can you find the best data visualization tools?

First off, get a handle on what kind of data you're dealing with – how complex is it, where's it coming from, you know the drill. Then, check if the tools you're eyeing can play nice with your data sources and handle the volume you're throwing at them. Think about how often you'll need to tweak your visualizations and if the tools can handle that rhythm. Make sure whatever you pick is user friendly and don't forget to think ahead – your project's gonna grow, so make sure the tools can grow with it. Get some input from folks who've used the tools, and give 'em a spin with any free trials they offer. And of course, keep an eye on the budget.

First, discover the resources of data that you'll be the use of in your project. This may assist determine the kind of information visualization tools that could high-quality suit your needs. Next, studies and examine specific gear to be had in the marketplace, paying attention to their capabilities, compatibility along with your information sources, and consumer reviews. It may also be useful to searching for recommendations from different professionals in your discipline or consult with a facts visualization professional. Sooner or later, take into account accomplishing an ordeal or demo of the top tools to determine which one is the simplest on your assignment.

Antes de avaliar a fonte de dados, é importante que você compreenda, junto com os envolvidos no projeto, o que buscam medir. Identificar as perguntas certas é essencial para obter as respostas necessárias, bem como definir os públicos-alvo e as possíveis dores que possam ter, a fim de mapear as fontes de dados adequadas. Apenas esse trabalho prévio ajudará o seu projeto a ganhar agilidade, reduzir retrabalhos e evitar insights que possam confundir a compreensão da ação. Neste caso, menos é sempre mais.

- Define your project goals, audience, and visualization needs. - Explore versatile tools like Tableau for powerful analytics, Power BI for user-friendly dashboards, and D3.js for customizable visuals. - Consider tools' strengths: Tableau excels in interactive exploration, Power BI in seamless integration, and D3.js in bespoke designs. - Evaluate collaboration features; Tableau Online supports real-time collaboration, while Power BI integrates with Microsoft Teams. - Tailor your choice based on the project's unique demands to ensure impactful data storytelling.

Explore user reviews and testimonials for practical insights. Test the tool's trial version to ensure it aligns with your project's unique needs. Look for tools with integrations that complement your existing workflow. Leverage online communities and forums like Stack Overflow for peer recommendations. Prioritize scalability for future growth. A comprehensive evaluation ensures the perfect synergy between your innovation project and the selected data visualization tool.

É sempre importante definir quais são as perguntas certas que fornecerão as respostas fundamentais para embasar o seu projeto de inovação. Geralmente, menos é sempre mais quando você consegue ser essencialista e assertivo na estratégia.

I would recommend to study Innovation management as developed by the ISO technical committee TC 279. ISO 56000 contains a series of standards some of which touch on methods. Practically, if data visualization or data interpretation is a challenge, run a survey, include all the team members and several suitable external members. The trick is to properly build the survey in such way as to hone in towards the most effective solutions which capture all kinds of variances but remember, simplicity is the ultimate sophistication. This can take a lot of time and effort but the results might be very rewarding.