You need to create a data-driven story. What are the best data visualization software options?

Tableau is a leading data visualization software known for its user-friendly interface and robust features. With intuitive drag-and-drop functionality, it allows users to transform raw data into compelling visualizations. Tableau supports a wide range of data sources and offers interactive dashboards, making it an ideal choice for exploring and presenting complex datasets. Its strong community support and regular updates contribute to its popularity among data professionals, enabling effective storytelling through visually appealing and insightful graphics.

At the end of the day, the graphics and visualizations are not for you, but rather for the audience. The key success criteria is that the audience understands the relevance. If you don't convey relevance, you will not succeed.

In general, when you need to present data to people with general software or intermediate informatic skills BI can be your best ally due to most of people know Microsoft interface and they will fell more conected with the commands and all the interface of Power BI

There are many popular data visualization softwares in the industry. Such as Tableau, Microsoft Power BI, Google Data Studio, D3.js, Qlikview and many more. Data visualizations have greater impact on major sectors like health, science,agriculture , disaster management, climate change, sales & marketing, e-commerce, etc. There are goals through data visualisation softwares like data research & analysis, decision making, communication along with reporting, storytelling, and monitoring. And, who are the audiences of these data visualization? May be executives, decision makers, data analysts, scientists, IT professionals, educators, presenters, researchers, business owners, stakeholders, etc.

1. Power BI - for its ease of usage even for beginners and easier integration across Microsoft 365 applications. 2. Tableau - for its range of features 3. Google Data Studio - for basic data visualization tasks especially when data resides in google sheets. 4. R language packages - for niche requirements of data visualization.

It is very important to know the data and the data sources for the specific problem/idea being presented, before presenting any story supported with data visualization.

The devil is in the details. Having an intimate knowledge of the data, where it comes from, how it's configured, etc. will be absolutely critical in presenting not only compelling data, but data that is accurate and tells the right story. As with all software, if the data going in isn't correct or accurate, the output won't be either. In that case, users are almost just as well off without it. Spend the first portion of your project understanding the nature of the data before putting it together, and verify that it's correct several times throughout the reporting process.

In addition to understanding the data landscape, a solid understanding of the process to capture the data and maintain the quality is critical. The data visualization will expose data quality issues, if they exist, eroding trust in the insights from the analysis.

It is not rare to see colours used for data visualization which are not well comprehended by people with paired vision - i.e. colour blindness. This should be taken into consideration when creating content, especially for a bigger audience, because then the odds are higher for people with paired vision.

All visualizations must be quickly understandable by the audience. If you have to explain what the visualization is, you have failed. It should be obvious to the audience.

When considering budget and skills for data visualization software, think strategically. If you're on a tight budget, explore free or open-source tools like Google Charts or Tableau Public. These might require more effort to master, but they offer robust functionality without the cost. On the other hand, if you have a budget but limited time for learning, look for more intuitive, subscription-based platforms like Tableau or Power BI, which offer drag-and-drop interfaces and extensive support resources. Remember, your choice should be a balance between financial investment and ease of use based on your technical proficiency. Consider not just the initial cost but also the time and resources required for learning and ongoing use.

Craft a compelling data-driven narrative with disruptive visualizations using software like Tableau, renowned for its intuitive interface and diverse chart options. Opt for strategic storytelling through Power BI, seamlessly integrating data insights into a cohesive narrative for impactful presentations. Embrace the creative versatility of D3.js, a JavaScript library, for custom, interactive visualizations tailored to your unique storytelling needs. Experiment with Flourish, a platform offering dynamic and visually appealing data presentations, adding a creative flair to captivate your audience.

Your mind is the most powerful visualisation tool in the world. Data visualisation software doesn't replace it or compensate for a lack of planned story-telling. Think intuitive decision-making visualisations driving actions and then choose your preferred visualisation software. Personally I love using Tableau to visualise insights and create interactive tools which intuitively drive action.

Power BI plays a pivotal role in the realm of data visualization storytelling by enabling users to create compelling narratives through data-driven insights. It empowers individuals and organizations to transform raw data into visually appealing and easy-to-understand presentations, fostering effective communication and decision-making. One of the primary roles of Power BI in data visualization storytelling is its capacity to create visually stunning and intuitive dashboards and reports. These dashboards serve as the canvas for presenting data in a coherent and impactful manner. Users can employ a wide array of customizable visualization elements such as charts, graphs, maps, and tables to represent data trends and comparisons

In today's technology evaluation, we have plenty of options available for data visualization. While Tableau provides rich options for analytics with heterogeneous data sources, it helps provide views and trends for better decision making. Additionally one can use various AI tools available for great analytics.

In my experience, it is essential to keep in mind the end goal of clearly communicating data insights to decision-makers when evaluating data visualization tools for a project.

I have to weigh in here, & disagree with Tableau. I use it & have used it at previous companies. I am a huge BI fan of Dynamics 365, I also have been fond of SAP. Back in the day my ‘go-to’ was Microstrategy; however, since that time other ERPs have come along & taken a front seat approach.

Here’s a dramatic thought. What if you don’t present any data at all? What if you don’t even have a presentation deck? Think about the top 3 insights the data has given you. Why are these important? Can you tell a story around them and weave this story into a potential future that changes things for the better? Now ask yourself if you really need a few slides to demonstrate it! I guess my point is : don’t hide behind a deck or software. Be human.

Before you make a decision, evaluate your specific needs, your team's expertise, and budget constraints. Explore trial versions offered by many of these tools to determine which one suits your requirements best for crafting a compelling data-driven story. Looking specifically at Google Data Studio: Key Features: Utilize a cloud-based platform for effortless collaboration. Integrate seamlessly with Google's suite of tools (Google Analytics, Google Sheets, etc.). Advantages: Access basic features for free. Particularly beneficial for teams using Google Workspace. Enjoy a user-friendly interface. Considerations: Compared to other tools, advanced features may have limitations.

Know what you are trying to accomplish with your visualizations. Is it to be informative or are you looking for a decision to be made. Align everything to be cohesive to that goal. Eliminate everything else.

Here’s a dramatic thought. What if you don’t present any data at all? What if you don’t even have a presentation deck? Think about the top 3 insights the data has given you. Why are these important? Can you tell a story around them and weave this story into a potential future that changes things for the better? Now ask yourself if you really need a few slides to demonstrate it! I guess my point is : don’t hide behind a deck or software. Be human.

En mi opinión es muy difícil presentar información generada de datos que tenemos por todo lado y en cantidades impresionantes y por desgracia presupuestos muy pequeños, para empezar elijan un equipo de varias áreas de la empresa y ponganlos a estudiar PowerBi, KissFlow y UiPath con el objetivo de generar una solución al final de cada curso de un mes, luego hacer un trabajo integrador que utilice por lo menos dos de las herramientas, el resultado desde el primer mes tendrá información relevante para tomar decisiones; al quinto mes las eficiencias serán imparables, luego podemos pasar a otras herramientas como phyton, a un programa de coach, mentoring, softskills, hardskills, según la necesidad que cada equipo o persona.