You’re an Information Systems professional. How can you take your data visualization to the next level? (2024)

Last updated on Feb 14, 2024

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Choose the right type of chart

2

Use colors and labels wisely

3

Add interactivity and animation

4

Use cloud-based collaboration software

Be the first to add your personal experience

5

Follow best practices and standards

6

Here’s what else to consider

Data visualization is a powerful tool for Information Systems professionals. It can help you communicate complex data, insights, and trends to your audience, whether they are clients, stakeholders, or colleagues. But how can you make your data visualization more effective, engaging, and impactful? Here are some tips to take your data visualization to the next level.

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  • Kevin Frye 🚀 Business Startup Guru | Entrepreneurial Mentor | Business Leader 🌐

    You’re an Information Systems professional. How can you take your data visualization to the next level? (3) 1

  • Bhavin Gandhi Technical Program Director | Drove $100M+ in revenue by bridging business and tech | Al/ML | MBA | MS in CS | PMP® |…

    You’re an Information Systems professional. How can you take your data visualization to the next level? (5) 1

  • Shakira S Chief Information Officer at TYCOONSTORY

    You’re an Information Systems professional. How can you take your data visualization to the next level? (7) 1

You’re an Information Systems professional. How can you take your data visualization to the next level? (8) You’re an Information Systems professional. How can you take your data visualization to the next level? (9) You’re an Information Systems professional. How can you take your data visualization to the next level? (10)

1 Choose the right type of chart

Not all charts are created equal. Depending on your data and your message, you need to choose the most appropriate type of chart to convey your information. For example, if you want to show proportions or percentages, a pie chart or a donut chart might be suitable. If you want to show trends or changes over time, a line chart or a bar chart might be better. If you want to show relationships or correlations, a scatter plot or a bubble chart might work. Think about what you want your audience to see and understand from your data, and select the chart that best supports that.

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  • Kevin Frye 🚀 Business Startup Guru | Entrepreneurial Mentor | Business Leader 🌐

    I've found that data can be very helpful, but I would add that simplicity matters. One well thought-out chart with a good explanation can be much better than three charts that might overwhelm. Control the conversation and use the chart as a starting point, not the end.

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  • Alexandra McCoy

    Choosing the right chart likely the most important step. When choosing your charts it is important to assess and understand your target audience. A dashboard reporting metrics for an engineering team is not going to be the same dashboard that management and executives are interested in. Take into consideration how much time the consumer has or wants to take when reviewing the chart. More than just picking the type of data you want to show, fully understand the data being consumed by the target audience or consumer.

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  • Tamshral Ul haq Assistant Category Manager | xNDURE |Category Head |Demand Planning |Buying Expert | Category Management

    To elevate data visualization, an Information Systems professional can leverage advanced tools like Tableau or Python libraries for more intricate visualizations. Incorporating interactivity such as tooltips and filters enhances user engagement. Storytelling techniques help contextualize data, making it more accessible. Integrating diverse data sources offers a holistic view. Advanced analytics techniques like predictive modeling unveil deeper insights. Custom visualizations tailored to specific needs and adherence to design principles further enhance visualization quality. These strategies collectively amplify the effectiveness and impact of data visualization efforts.

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  • When it comes to visualization* Withy overwhelming options of visualizations, picking the one which is simple and conveys the keys idea is the key.* Presence of User interactivity via drill down and drill through helps.

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2 Use colors and labels wisely

Colors and labels play an important role in data visualization, as they can help to highlight key points, create contrast, and draw attention. However, they can also cause confusion, distraction, or mislead your audience if used inappropriately. To ensure that colors and labels are used effectively, it is important to use a consistent color scheme that matches your brand or theme. Contrasting colors should be used to emphasize differences or categories and colors should be easy to distinguish and not too numerous. Labels should be clear, concise, accurate, aligned, legible, and readable. Additionally, it is important to avoid using colors or labels that have negative or misleading connotations.

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  • Bhavin Gandhi Technical Program Director | Drove $100M+ in revenue by bridging business and tech | Al/ML | MBA | MS in CS | PMP® | CSM® | SAFe®

    Color coding might seem simple, but it can significantly transform reporting and boost its effectiveness. For example, at one of the AI companies, we measured various team metrics to improve their productivity, such as average velocity, say/do ratio, total features released, and total bugs found. To make these metrics more impactful, I suggested introducing color coding. Any deviation from the average by less than 20% would be highlighted in yellow, while deviations above 20% would be in red. These visual cues increased collaboration with the executive team, making them more interested in a detailed analysis of teams that needed support. And hence, Eng Ops review adopted this color coding approach across all teams.

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3 Add interactivity and animation

Interactivity and animation can add an extra layer to your data visualization, making it more dynamic, interactive, and engaging. It can also help reveal details, show different perspectives, and tell a story with your data. For instance, interactivity and animation can enable your audience to explore, filter, or zoom in on your data. It can also illustrate how your data changes over time or in response to different scenarios. Plus, it can highlight patterns, outliers, or anomalies in your data and create transitions, effects, or annotations that guide your audience through your data.

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  • Timothy Morgan Project Management to Project Mastery | Rethinking PM tools to get more done with less effort. Making project management accessible to everyone.

    Building interactivity into a visualization can allow for self-service for your audience, and can impress. Instead of needing to tailor a set of visualizations for different purposes (or for different target audiences) you can elegantly display the information, and allow the user to explore the information. A well-designed tool can reduce the need for many additional tools. And will also leave a user more impressed than a static graph or chart.

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4 Use cloud-based collaboration software

Cloud-based collaboration software can offer you several advantages when creating, sharing, and updating your data visualization. It allows you to connect with your team, gain feedback, and refine your data visualization. With cloud-based collaboration software, you can access your data and data visualization from any location and device, sync it automatically and securely, invite team members to view, edit, or comment on it, embed it on your website or blog, and track the performance and impact of your data visualization.

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5 Follow best practices and standards

Data visualization is not only an art, but also a science. To ensure the quality, accuracy, and credibility of your data visualization, you should use reliable and relevant data sources and cite them properly. Additionally, it is important to clean and prepare your data before visualizing it. Furthermore, check your data visualization for errors, inconsistencies, or biases and use appropriate scales, axes, and legends for your charts. Additionally, when dealing with sensitive or personal data, follow ethical and legal principles. Finally, test your data visualization with your audience and get feedback. By following these tips, you can take your data visualization to the next level and impress your audience with your Information Systems skills.

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  • Shakira S Chief Information Officer at TYCOONSTORY

    Data science is gaining importance these days. Data visualization tools are all about gathering raw data and converting the same into visuals. Being visual creatures, viewers can find colorful graphics to be quite appealing. Businesses can also convey messages quite easily and more effectively unlike plain numbers.Visuals also provide valuable information that can be absorbed effortlessly. It also helps specific datasets to become more appealing to users. Incorporating the same into business does not require any expertise. You just need to use the right tools and develop attractive charts, maps, diagrams along other visuals.

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6 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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  • Shakira S Chief Information Officer at TYCOONSTORY

    Top 10 Data Visualization Tools1. Tableau Public & Gallery2. HockeyStack3. Google Charts4. Google Data Studio5. Infogram6. Datawrapper7. D3.js8. Flourish Public9. RAWGraphs10. Dygraphs

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  • Max Kul QA Engineer | Software Testing|Multilingual Professional

    As an Information Systems professional, there are several ways to take your data visualization to the next level, but I assume there is one above others to consider.Focus on user experience: Ensure that your visualizations are easy to understand and navigate. Pay attention to the design, layout, and color schemes to make the data more accessible and visually appealing.

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Information Systems You’re an Information Systems professional. How can you take your data visualization to the next level? (86)

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