What are the best ways to teach data visualization and storytelling to employees?

Imagine. Imagine and Imagine. Just for 30 mins. What you would like to hear and what you would not like to hear. Make a fictitious story without data, assumptions, or anything. One story for good scenario, one story for worst scenario and one for worst. You will be surprised how much it then it will help you in doing things mentioned in the points there. Example of a story: our company name is on WSJ front page because the net revenue is more as customer experience is rated highest etc.

Muitos profissionais de fora da área de dados sabem criar visualiza??es e dashboards. Entretanto, fazem isso de forma instintiva e n?o seguindo uma metodologia. Antes de criar gráficos é importante saber como usá-los da maneira correta, por isso considero que uma das melhores maneiras de ensinar alguém a criar visualiza??es é incentivando a estudar Estatística Descritiva para aprender sobre tipos de variáveis, medidas, tipos de gráficos e etc.

In order to effectively teach data visualization and storytelling, firstly start by assessing employee's current data literacy and visualization skills. Take Employe surveys, interviews, or tests to identify gaps and challenges. Tailor training content and format based on these insights. Segment employees into groups based on roles or interests, offering customized training at different levels. This needs assessment ensures a targeted and relevant approach, maximizing the impact of the training program.

It is critical to assign training to employees based on their existing knowledge. Conducting a survey or test to determine each employee's skill level is one useful way. As a result, employees may be classified into three groups: beginners, intermediates, and advanced. Other approach can be to provide a?initial?fundamental training session for everyone to guarantee uniformity. Following that, dividing them into groups containing different curriculum related to data visualisation according to their roles and functions would be beneficial and save time.

In my experience, the most effective way to gauge how informed your peers are in the realm of visualization is to individually ask each of them to visualize a dataset, showcasing a specific fact within it. ?? Afterward, review and assess the visualizations they create. You can further discuss each visualization anonymously and then privately share the relevant facts with your peers. ?? This approach not only promotes a better understanding of their visualization skills but also allows for constructive feedback and improvement. ??

I remember my first Data Analysis project was on the COVID-19 dataset from Kaggle back in 2019. I would recommend practicing with a trending Dataset on Kaggle. Working on Real Data is motivating as it gives you the confidence to work on real problems. - Start by having a general understanding of the different kinds of Visualisation Plots and their strengths. - Now experiment with different plots for your insight from the dataset and compare which plot conveys the point more accurately. - If you are using Python, Adding styles and colors to basic MatPlotLib plots using a mixture of Seaborn also adds colors to your analysis!

Imagine you're analyzing sales data for a retail company. Instead of using generic examples, you could use specific figures like "In Q4 2023, the company experienced a 15% increase in overall sales compared to the previous year, driven by a 25% surge in online sales."By incorporating real numbers and timeframes, your data storytelling becomes more compelling and concrete, helping your audience better understand the significance of the insights. This approach enhances the credibility and relevance of your data-driven story.

Integrate real data into your training by utilizing authentic organizational datasets related to your industry or specific challenges. For instance, leverage genuine customer profiles, purchase histories, or feedback data if your company deals with customer demographics. This direct connection to workplace scenarios enables employees to apply their learning in practical contexts or they can also use RWFD as well. Explore relevant case studies from your industry to showcase the positive impact of effective data visualization and storytelling in similar business settings. This approach not only reinforces key concepts but also inspires employees by illustrating the tangible benefits of mastering these skills in real-world situations.

It is essential to incorporate the teaching of data visualization and storytelling using real data. Understanding the background of the data contributes to a more profound comprehension of the output, facilitating the evaluation process and enhancing creativity. Various employee groups may generate distinct types of visualizations that are more accessible and beneficial in the context of their work. Utilizing real data encourages the application of diverse techniques, offering valuable insights, as real datasets are often imperfect, extensive, and unevenly distributed across space and time.

To further ignite passion among peers, consider organizing a data-driven contest within the firm. ?? This competition not only guarantees that peers will strive for excellence in the given task but also fosters eagerness to participate and potentially sparks a newfound interest in becoming experts at visualization. ?? The thrill of a friendly competition can transform tasks into exciting opportunities for skill development and professional growth. ??

Emphasize the WHY in data visualization and storytelling training. It's crucial for employees to grasp the purpose and value, understanding how these skills solve problems, answer questions, and persuade audiences. Guide them in selecting appropriate visualizations, relevant data points, and compelling narratives tailored to their context. In addition, educate them on steering clear of common pitfalls and biases that could compromise data credibility and clarity. By instilling a deeper comprehension of the rationale behind these practices, employees can harness data effectively, enhancing their decision-making and communication abilities.

To effectively teach data visualization and storytelling, emphasize the "why": the purpose and impact of visualizing data. Start by explaining how these skills aid in making informed decisions and communicating insights. Use real-world examples to illustrate their practical value. Conduct interactive workshops for hands-on experience, focusing on choosing visualizations that best convey the story behind the data. Encourage employees to think about the audience and the narrative they want to present, and provide regular feedback to refine their approach.

On my perspective, emphasizing the "why" is literally the most important step in any training, specially when it comes to technical topics such as data visualization and tools. If you show people the value behind improving the storytelling through meaningful visualizations, they'll start to operate that way without you having to step up every time. Guiding them to adapt data viz techniques can be difficult, but if you explain the reason behind skills such as bias identification, data credibility and clarity, common pitfalls etc it will for sure make them pay more attention and use it in their day-to-day life.

Many businesses, like the New York Times, utilize data visualization to highlight significant trends for a non-technical audience. For example, during the COVID-19 outbreak, data visualization made it easier for the public to understand the spread of the virus, number of cases, and impact on different geographical areas. Businesses integrate data storytelling techniques into their marketing strategies to better connect with customers, often using graphs or charts to illustrate product performance, customer behavior, or market trends. Knowledge of these techniques helps employees present complex data in a comprehensible and appealing manner.

I prefer emphasizing "starts with why" rather than solely concentrating on it. In the end, data visualization and storytelling represent just one avenue for gaining valuable insights from analysis. Nevertheless, the initial questions to consider are: Why am I undertaking this analysis? What kind of analysis do I want to conduct? Who is the ultimate audience for this analysis?

Empower your employees in data visualization and storytelling by fostering a continuous learning environment. Offer regular opportunities for practice and improvement, providing constructive feedback through methods like peer review or coaching. Establishing a supportive community of practice enables employees to share their data stories, learn collectively, and celebrate accomplishments.

For example, in many software companies like Adobe and Autodesk, regular workshops and webinars are organized for employees to improve their data visualization and storytelling skills. To make it more engaging, they often hold in-house competitions to encourage employees to showcase their skills in a low-pressure environment. The better visualizations and stories are recognized publicly, providing both motivation and a clearer understanding of what good data storytelling looks like. These practices foster a collaborative environment where learning and skill-building become part of the company culture.

Em minha experiência como professor, por mais que eu soubesse que um conteúdo foi "bem" explicado, ainda haveriam aqueles que teriam dificuldade, pelo simples medo de "errar". Mas aprender é um processo contínuo, que n?o depende de uma única explana??o, e quando falamos de visualiza??o, leva algum tempo para entendermos melhor o quanto aquilo é ou n?o é eficaz. é um processo contínuo, que deve ter abertura para além de uma única conversa em um workshop!

a good way is to do regular workshop sessions with interested people about a specific data set and give all the freedom do experiment with different viewpoints and afterwards present every viz to the group and explain your why and way of viz. this way the company can work out their own best practices that meet their needs like templates and guide lines. if the budget is tight I can highly recommend makeovermonday (book or yt) to see some examples of good viz for different data and their messages.

Establish a STRUCTURED peer review system for ongoing feedback. This encourages COLLABORATION and continuous learning, enhancing skill development in a supportive environment.

Encouraging creativity and experimentation is pivotal in creating a dynamic learning environment for data visualization and storytelling. By providing the freedom to explore innovative approaches, we can encourage and uncover unique insights as well as refine storytelling skills. This approach not only helps enhance creative thinking but also instills a sense of ownership to each individual in the learning process, ultimately contributing to a more effective and engaging training experience.

Encouraging the experimentation and creativity of employees is highly crucial. It contributes to the continuous growth of their skills and enriches the entire technological stack of the company. Instead of prescribing how to do something, inquire about what needs to be done. You'll be surprised by the autonomy, creativity, and innovation employees can demonstrate. Initiatives like hack days or knowledge-sharing sessions within the company provide opportunities to challenge employees, prompting them to explore new techniques and fostering flexibility in choosing toolchain.

La narración de historias es un arte, y como tal, es muy difícil de ense?ar. Si bien contar tu fuente de inspiración y cómo elaboras tus narraciones es una base para que cada uno de los alumnos encuentre su vía para crear narraciones.

For instance, Google encourages it's employees to dedicate 20% of their work time on side projects, leading to notable outcomes like Gmail and Google News. Similarly, Netflix's "Hack Day," allows employees to experiment with new ideas for one full day. Adopting such practices can stimulate curiosity and promote data exploration, leading to innovative data visualizations and compelling storytelling. Practice environments, like these, not only help develop skills but also nurture a spirit of ongoing learning and improvement.

Encorajar experimenta??o e criatividade é crucial para estimular a inova??o e o desenvolvimento de solu??es originais. Isso amplia perspectivas, impulsiona a resolu??o de problemas de maneiras únicas e promove a descoberta de abordagens eficazes, essenciais para avan?os significativos em qualquer campo. A utiliza??o das práticas e das metodologias é importante para dar ferramentas para os colaboradores come?arem a desenvolver suas visualiza??es de forma eficiente. A partir dessa "funda??o" de conhecimento, permitir que as pessoas testem e pensem em alternativas n?o padronizadas é o que realmente desenvolve novas solu??es aderentes as necessidades de cada área da empresa.

-Design structured training modules that cover the fundamentals of data visualization, including types of charts/graphs, visualization tools, and principles of compelling storytelling with data. -Use real-world examples and case studies relevant to your industry or company. Show successful data visualizations and storytelling techniques to illustrate their impact. -Provide hands-on workshops where employees can practice creating visualizations. Assign exercises encouraging them to work with datasets to visualize and communicate insights. -Offer training sessions focused on popular data visualization tools like Tableau, Power BI, or Python libraries (Matplotlib, Seaborn) to ensure employees are comfortable using these tools effectively.

An uncommon method to teach data visualization and storytelling is to conduct what I call a "Silent Data Session." In this approach, present a complex dataset to people without any verbal explanation. Challenge them to interpret the data and craft a story solely based on the visualizations provided. This exercise sharpens their ability to discern narratives from data visually, encouraging creativity and a deeper understanding of how effectively designed visuals can communicate complex information. This method emphasizes the power of visualization in storytelling, without relying on verbal or written cues. It also helps people recognize their biases when attempting to construct a story from data.

A valuable approach I've discovered is investing in teaching employees visualization skills by providing essential materials such as books, courses, and even sponsoring bootcamps. ???? However, it's crucial to recognize that the most pivotal factor in effective visualization education is the passion of the employees for learning. ?? Strive to cultivate that passion by creating an engaging and inspiring learning environment. When employees are genuinely enthusiastic, the process of mastering visualization becomes not only educational but also enjoyable. ??

Considere que nem todo mundo possui o mesmo background técnico que você, portanto, comece com o básico, como tipos de gráficos, tabelas e conceitos iniciais. Depois forne?a exemplos e exercícios práticos próximos da realidade desses usuários e do tipo de dados com que eles lidam diariamente. Com uma linguagem simples e acessível, o aprendizado fica divertido e envolvente, tornando mais agradável para o receptor. E por último, é importante deixar o aprendizado em aberto, ou seja, que o receptor busque cursos, livros, vídeos, que possam agregar ao que foi ensinado.