Last updated on Feb 17, 2024
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Know your goals
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Explore your data
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Compare your options
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Test your results
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Here’s what else to consider
Data visualization is the art and science of presenting data in a clear, engaging, and meaningful way. It can help you communicate your insights, persuade your audience, and reveal hidden patterns and trends. But how can you find the right tools for the job? Here are some tips to help you choose the best software for creating and managing your reports.
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- Carlos Zepeda Director, Interconnection, Passive, and Electromechanics Division, Engineering Services, and Demand Creation for the…
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- Manel Digón KAM Distribuidores ( Catalunya, Andorra y Ibiza )
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1 Know your goals
Before you start looking for data visualization tools, you need to have a clear idea of what you want to achieve with your reports. What is the main message or question you want to answer? Who is your target audience and what are their needs and preferences? How will you distribute and update your reports? These questions will help you define your goals and narrow down your options.
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Understanding the message to be delivered is a good start point to determine which tools to be used and how to be utilized effectively. It is important to emphasize on a take-away message in a clear and convincing manner.
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- Manel Digón KAM Distribuidores ( Catalunya, Andorra y Ibiza )
El análisis de los datos es crucial para abordar cualquier negociación. Con una metodología exhaustiva y eficaz de trabajo el éxito está garantizado.
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- Ehab Amr Sr. BIM Coordinator | VDC | 8x Linkedin Top Voice
By understanding the desired outcomes, data can be tailored to address specific objectives, ensuring relevance and usefulness. This knowledge helps in selecting appropriate data sources, defining key metrics, and designing meaningful analyses that align with the overarching goals. Ultimately, leveraging insights from data in line with the goals enhances decision-making, drives strategic initiatives, and fosters business success
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Data visualization is to communicate insight from data more quickly to the viewer and to make trends more apparent. Choose the right type of visualization or chart for your data which is easy to understand at 1st sight.Use text and labels to clarify not to clutter, so less questions.Use colour to highlight important information or to differentiate or compare.Avoid misleading visualizations.Keep your visualizations simple. Less is more.
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- James Corbett Business Process Manager at Endress+Hauser Group | Driving Business Efficiency
Understanding your visualization goals is paramount. Are you aiming to inform, persuade, or explore your data? The purpose dictates the choice of tool. Informative visuals might need straightforward tools like bar or line charts, persuasive visuals could benefit from more dynamic tools like interactive maps or animations, and exploratory visuals require software with capabilities for data manipulation and detailed analysis. Define your audience, message, and the action you wish your audience to take after viewing the visualization.
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- Flávio Coelho Supervisor Diamante Vendas e Execução na The HEINEKEN Company
Ao explorar diferentes ferramentas, é importante considerar suas necessidades. Se você tem facilidade na parte visual , procure ferramentas com interfaces intuitivas. Se estiver confortável com uma abordagem mais prática, as plataformas que oferecem personalização por meio de codificação podem ser uma boa opção. Tão logo sua evolução pedira a cada dia um nível melhor de entendimento e assim poderá ser mutável suas necessidades.
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When we understand the desired outcomes, we can customize the data to address specific objectives, making it relevant and useful. This knowledge allows us to choose the right data sources, define key metrics, and design meaningful analyses that align with our overarching goals. By leveraging insights from data in line with our goals, we can enhance decision-making, drive strategic initiatives, and ultimately achieve business success. It's all about using data as a powerful tool to guide us towards our desired outcomes! 📊💼
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2 Explore your data
Next, you need to understand your data and how it can be visualized. What type of data do you have (quantitative, qualitative, categorical, etc.)? How much data do you have and how complex is it? What are the key variables and relationships you want to highlight? How can you transform, filter, or aggregate your data to make it more relevant and useful? These questions will help you explore your data and select the most appropriate charts, graphs, maps, or other visual elements.
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- Lisandro Siqueira Médico Ocupacional
Diferenciar si quiere mostrar la evolución de una variable, la relación con un todo, si se relacionan o no entre variables, o como se agrupan en clases.
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When it comes to analyzing data, we can differentiate based on what we want to explore. If we want to show the evolution of a variable over time, we can use time series analysis to track its changes. If we're interested in understanding the relationship between variables, we can use techniques like correlation or regression analysis. On the other hand, if we want to see how variables are grouped into classes or categories, we can use techniques like clustering or classification. Each approach helps us gain insights into different aspects of the data and allows us to make informed decisions. So, depending on what we want to explore, we can choose the right analytical approach! 📊🔍
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Utilizing advanced data exploration platforms enables you to sift through various data types, uncovering valuable insights nestled within your datasets. Imagine the process of transforming and manipulating large datasets to bring to light key relationships or trends that can significantly impact decision-making. For instance, consider a scenario where a retail company delves into its sales data to uncover purchasing trends, leading to optimized inventory levels and improved customer satisfaction. Such real-world applications underscore the importance of deep data exploration, making your findings not only more relevant but also ensuring that your visualizations are anchored in substantial, actionable insights.
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Based on my personal experience having an in-house analytics department and implementing software tools for data rearrangement is crucial. Once you have identified the questions you want to address, it's time to explore your data and identify key factors that can depict the most general scenario. From there, you can begin asking more detailed questions and refining your data by cleaning it. Eventually, you'll find an arrangement that either provides the answers you seek or, over time, offers the clarity you need.
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- Elizabeth Bravo Cestari Autónomo
La importancia de los datos. Y de cómo se presentan . E este caso las referencias anteriores son importantes, como eran? Cómo son? Que dificultades presenta a los usuarios? Que es lo realmente importante de mostrar? No solo para el equipo si no para el usuario final . Que tipo de datos e imágenes son más amigables y comprensibles para tus interlocutores
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3 Compare your options
Once you have a clear vision of your goals and data, you can start comparing different data visualization tools. There are many factors to consider, such as the features, functionality, ease of use, cost, support, compatibility, and security of each tool. You can use online reviews, ratings, demos, or free trials to evaluate and compare your options. You can also ask for recommendations from other data analysts, experts, or peers who have used similar tools.
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When exploring the vast array of available tools, consider those with intuitive interfaces that cater to users who value ease of use, as well as platforms that offer a high degree of customization for those who are comfortable with a more hands-on, coding approach. It's crucial to weigh not only your immediate needs but also consider how these tools will scale with your projects over time. A startup, for example, might lean towards solutions that offer cost-effectiveness and seamless integration with existing digital ecosystems. Sharing insights from professionals who have navigated these decisions can offer valuable perspectives, guiding you to the tool that best aligns with your project's scale and complexity.
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- Mohammad Nasr, PMP, SP Civil Engineer (PMP, SP) | Planning | Construction Management | Infrastructure | Seeking new Opportunities
To find the right tools for creating an effective data visualization you should consider : 1. Type of data.2. The desired output format.3. Ease of use and available features. 4. Evaluate each tool based on your specific project requirements to make the best choice to use.
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When exploring different tools, it's important to consider your preferences and needs. If you value ease of use, look for tools with intuitive interfaces. But if you're comfortable with a more hands-on approach, platforms that offer customization through coding might be a good fit. It's also crucial to think about scalability. Will the tool grow with your projects over time? For startups, cost-effectiveness and seamless integration with existing digital ecosystems are key factors to consider. And don't forget to seek insights from professionals who have been through similar decisions. Their perspectives can guide you to the tool that aligns best with your project's scale and complexity. Happy tool hunting! 🛠️🔍
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When comparing data visualization tools, several factors are crucial to consider, including features, functionality, ease of use, cost, support, compatibility, and security. Utilizing resources like online reviews, ratings, demos, and free trials can facilitate evaluation and comparison. Seeking recommendations from other data analysts, experts, or peers who have experience with similar tools can provide valuable insights into their effectiveness and suitability for your specific needs. By carefully assessing these factors and leveraging available resources, you can make an informed decision in selecting the most suitable data visualization tool for your requirements.
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- Zakaria Lebhal P2P Accounts payable specialist
📊 Exploring data visualization tools is like embarking on a thrilling quest for me! 🌐 Once I had my goals and data in focus, diving into the myriad of tools felt both challenging and exhilarating. From grappling with features to weighing the nuances of cost and security, every choice felt like sculpting my analytical toolkit. 🛠️ Online reviews and tapping into the wisdom of fellow data aficionados became my compass in this adventure. Here's to the rewarding journey of turning raw data into meaningful insights! 🚀
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4 Test your results
Finally, you need to test your data visualization results and see how they perform in practice. You can use various methods, such as feedback, surveys, analytics, or usability testing, to measure the effectiveness, clarity, accuracy, and appeal of your reports. You can also check for errors, inconsistencies, or biases in your data or visuals. Based on your findings, you can refine, improve, or change your data visualization tools or techniques.
Data visualization is a powerful skill that can enhance your decision-making process and impact. By following these tips, you can find the right tools for the job and create stunning and informative reports.
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After crafting your visualizations, the next step is to test their impact. Implementing a feedback loop where stakeholders can share their insights on the clarity and effectiveness of your visualizations is invaluable. For example, using A/B testing to compare two versions of a visualization can reveal preferences and usability issues not previously considered. Additionally, tracking engagement metrics through tools like Google Analytics can provide quantitative feedback on how your visualizations are being interacted with. This iterative process, enriched by both qualitative and quantitative feedback, ensures your visualizations not only convey the intended message but also resonate with your audience on a deeper level.
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Es importante tener claridad en el objetivo meta para que de esta manera se puedan realizar los ajustes correspondientes en los informes y realmente se logre el impacto por el cual se realizo la implementación del informe.
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- Alireza Kia ✔ Software Engineer: (Full Stack .Net Developer | C# | SQL Programming | BI Dashboard) 💠→ Network Engineer: (CCNA,CCNP,MCSE,VMWare,Linux)
Concluding the process, it's crucial to test the efficacy of your data visualization. Utilize methods such as feedback, surveys, analytics, or usability testing to gauge the performance, clarity, accuracy, and visual appeal of your reports. Scrutinize for potential errors, inconsistencies, or biases in both the data and visuals. Based on your findings, refine, improve, or consider changes to your data visualization tools or techniques.Mastering data visualization is a potent skill that significantly influences decision-making. By adhering to these guidelines, you can pinpoint the optimal tools, ensuring the creation of impactful and insightful reports.
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- Thanny A. Experienced Project Controls (Cost and Schedule and Risk management) professional
Evaluating the practical performance of data visualization outcomes requirestechnical validation, user input, and ongoing improvement. The objective is to guarantee that the visualizations faithfully depict the fundamental facts, are readily understandable to the targeted audience, and successfully convey the desired message or insights.Forexample, financial analysts may design a dashboard displayingquarterly sales patterns over the last five years. Toverify the precision, the analyst compares the displayed revenue numbers with the actual financial reports and conducts random checks using a spreadsheet to confirm the correctness of all calculations and aggregations.
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- Shehza Ashraf Data Scientist | Analytics | Business Intelligence | Machine Learning | Automation | Expert in Sequel
Testing your results is important for finding the right tools for creating effective data visualizations because it allows you to see how well the visualization communicates your message. By testing different visualization tools and techniques with your data, you can evaluate how clear, understandable, and impactful the visualizations are. This helps you identify any shortcomings or areas for improvement before finalizing your visualization. Testing also allows you to gather feedback from others, such as colleagues or stakeholders, to ensure that the visualization effectively conveys the intended message and meets their needs.
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5 Here’s what else to consider
This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?
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- Izaskun Ortiz Human Resources Director HR, Recruiter, People Development Management at AGUI
Buen artículo! Si me permites añadir, añadiría un punto en el que se diagnostica el nivel de cultura digital de los trabajadores. A veces queremos imponer y trabajar en nuevas tecnologías y la temperatura de nuestro clima laboral entorpece el proceso. Realmente estamos preparados? Cómo podemos saberlo? Que vamos a hacer para ello?
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- Nevine Roushdy 30+ years of Banking Experience | Change Management | Organizational Transformation | Governance | People Management | Strategy Management | EBI Registered Instructor
In my field it is very useful to use comparison of results either within similar periods across the year or current versus last year This make picture clearer and assist in decision making and planning for future actions
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Communicate, Community Participation and Motivation:Upon integrating enhancements based on feedback, ensure continuous communication of improvements. Encourage community participation in the refinement process by allowing contributions of data or tools. Additionally, introduce gamification to motivate involvement. This strategy not only keeps the community informed but also actively engages them in the development process, making it more collaborative and dynamic.
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- Julieta López Olalde Experta en comunicación educativa y para marketing.
Al trabajar en la comunicación de datos no debemos perder de vista a quién nos dirigimos. Quiénes elaboran gráficos tienen un predominio de las inteligencias relacionadas con la abstracción y la comprensión de las formas, así como una preparación en temas matemáticos. Si el público al que se dirige no tiene estas características es probable que la interpretación sea errónea o no se dé. Por eso me parece importante añadir la importancia de acompañar de textos e imágenes la visualización de datos, para atender a los distintos perfiles de inteligencia.
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- Naresh Kakar Human Resources Professional
To have proper data with a clear idea of achievement.Avoiding oversized data by carefully choosing pieces of information.Using a histogram or bar chart when comparing the difference between data sets and using line chart, scatter plot and box plot for larger variations.Considering breaking up data into smaller and more digestible pieces and using a variety of smaller charts to explain big ideas.Should pick a colour scheme and stick with it without having bad contrasting.To captivate attention there should be a bit of motions into the presentation and data visuals.It is important to let graphical display speak for itself rather than having more text.To be time efficient designing process should go as smoothly as possible.
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