Here's how you can incorporate strategic thinking into data visualization projects.

In my perspective, strategic thinking is essential for data visualization projects to thrive. By aligning these projects with organizational goals and understanding stakeholder needs, we ensure our visualizations drive informed decision-making. Prioritizing high-impact areas and considering long-term implications create sustainable value. Effective communication and iteration guarantee our visualizations shape the organization's strategic direction.

Ao iniciar o processo de visualiza??o de dados, é fundamental estabelecer metas claras e objetivas. Reflita sobre o propósito da visualiza??o e seu público-alvo para garantir comunica??o eficaz e escolhas de design pertinentes.

From my viewpoint, strategic thinking plays a vital role in the success of data visualization endeavors. By linking these projects with organizational objectives and grasping stakeholder requirements, we ensure that our visualizations facilitate well-informed decision-making. Emphasizing critical areas and contemplating the long-term consequences establish lasting value. Clear communication and continual refinement ensure that our visualizations influence the strategic trajectory of the organization. make sure goals should be clear as soon as possible for better experience for everyone

Para incorporar o pensamento estratégico em projetos de visualiza??o de dados, é essencial definir metas claras e mensuráveis. Comece entendendo o contexto e os objetivos do projeto, identificando os KPIs relevantes e estabelecendo metas SMART (Específicas, Mensuráveis, Atingíveis, Relevantes e Temporais). Isso garante que a visualiza??o seja direcionada e eficaz na comunica??o de informa??es importantes.

Understanding the data requires a certain aptitude to getting your hands dirty with the details of the domain. If the data you're working with is riddled with noise, censorship(political need-to-know or otherwise), or bias then modelling this data will be a challenge until one begins to shape it such that it conveys some sort of coherence. If the quality of the data is under question, either because of the above factors, then a general recipe of Domain-expertise -> Ground truth V&V -> cleaning/preprocessing/shaping can be applied. Domain expertise here can also be freely interchanged with existing Models even if they may be outdated, as existing models can still be used as a crutch in case domain expertise is not immediately available.

Understanding data is foundational in today's information-driven world. It involves more than just collecting and storing information; it requires the ability to interpret, analyze, and derive insights from vast amounts of data. By understanding data, we can uncover patterns, trends, and relationships that can inform decision-making, drive innovation, and solve complex problems. Moreover, data understanding enables us to identify opportunities, mitigate risks, and optimize processes across various domains such as business, healthcare, finance, and beyond. In essence, data understanding empowers individuals and organizations to harness the full potential of data to achieve their goals and make informed decisions in an evolving landscape.

"Numbers are numbers" - Famous last words - Sure, you can identify outliers, create thresholds using standard deviations, and callout trends without fully researching and understanding data. The real value comes from learning relationships, observing the methods of data capture, and seeing what processes are influenced by the data. Only after living in the data can you create a visual that provides actionable value to your stakeholders and not just another view of numbers.

Choosing the right type of chart can make the difference between success and failure in data visualization, but it is not the only factor to consider. Sometimes a table or text conveys the same information. Font size, background, data bars, line colors, legends and titles make up the choice in creating a visual.

Creating inclusive visualizations involves careful color selection to ensure accessibility for individuals with color blindness while maintaining visual appeal. Avoiding sole reliance on color, integrating patterns, labels, and diverse line styles can aid differentiation for those with color deficiencies. Employing color palettes with adequate contrast enhances readability for all users. Thoughtful design fosters engaging visualizations accessible to everyone, ensuring effective data interpretation and insight derivation.

Different charts excel at conveying specific information...... Line graphs for trends, bar charts for comparisons, pie charts for proportions, heatmaps for density and so on.....

Intent matters! With visuals, you need to know the intent. If you are looking at a business health metric, what problem are you trying to solve? If you want to identify contributors to low performance of a business channel, you might want to build an outlier view. If you are considering staffing levels through the holidays, you might want a line graph with YoY comparisons to help determine this years strategy. These types of questions can be answered initially in the scoping and understanding stages of project planning and contribute to the success of your view.

To tell a story,first, you must know your audience, understand how they think, and what their interest in the information is. The next step is to understand the context of the data, in order to develop a suitable presentation. Keep the visual clean and work on the design, to direct the audience and their interest to where you want, transmitting what the data revealed.

Good data visualization is akin to storytelling, guiding viewers through the data in a coherent and compelling manner. Each element of the visualization plays a role in narrating the story hidden within the data, from the choice of charts and graphs to the color scheme and layout. Just as a well-crafted story captivates its audience, effective data visualization captures attention, sparks curiosity, and communicates complex information in an understandable format. By carefully designing visualizations that tell a clear and engaging story, we empower viewers to uncover insights, make informed decisions, and take action based on the data presented.

Storytelling through data is one of the most engaging aspect with viewers and users. Apparently viewers have to find a solution by visualizing the dashboards and insights which you have generated from raw data. This can lead to increase the growth of customers and revenue in your business. Alternatively storytelling plays crucial role in attracting the customers through their dashboards and data-driven insights as per the need of stakeholders. Finally we have to follow the customer-centric approach in Storytelling to reach the wealth number of clients.

Incorporar o pensamento estratégico em projetos de visualiza??o de dados envolve contar uma história coesa e envolvente com os dados. Isso inclui identificar a mensagem principal, criar uma narrativa com come?o, meio e fim, contextualizar os dados, orientar a narrativa para a a??o e adaptar a história ao público-alvo. Contar uma história com os dados torna a visualiza??o mais significativa e envolvente, levando a uma melhor compreens?o e uso dos dados pelos usuários. Recomenda??o: Storytelling com dados: um guia sobre visualiza??o de dados para profissionais de negócios - Cole Nussbaumer Knaflic

Considering the broader context is crucial for effective data visualization. Cultural, economic, and social factors influence how audiences interpret data. By keeping the end user in mind and tailoring visualizations accordingly, designers ensure relevance and impact. Contextual awareness enhances understanding and facilitates informed decision-making, contributing to meaningful insights and actions.

Mastering the art of data visualization takes time, study and attempts. Don't be afraid to make mistakes, make mistakes and change quickly, adapt to feedback and refine your approach.

The initial visualization is a starting point not the final product. Being open to feedbacks and refining our work based on audience response and new information helps refinement....

Paying attention to visual design elements like color, font and layout is required...... These elements can significantly impact the effectiveness of our visualization.