What are the latest trends and innovations in data presentation and how do you keep up with them?

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Data presentation is the art and science of communicating data insights effectively and engagingly. Whether you are a data analyst, a business professional, or a curious learner, you need to keep up with the latest trends and innovations in data presentation to make the most of your data stories. In this article, we will explore some of the current and emerging developments in data presentation and how you can stay on top of them.

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1 Interactive dashboards

One of the most popular and powerful ways to present data is through interactive dashboards. Dashboards are visual displays that show key metrics, trends, and comparisons at a glance. They allow users to filter, drill down, and explore data according to their needs and interests. Interactive dashboards can be created using various tools and platforms, such as Tableau, Power BI, Google Data Studio, and more. They can also be embedded into websites, apps, or reports to enhance the user experience and engagement.

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2 Data storytelling

Another trend that is gaining momentum in data presentation is data storytelling. Data storytelling is the process of using data, visuals, and narrative to convey a clear and compelling message to an audience. Data storytelling goes beyond just showing data; it involves crafting a story arc, choosing the right visuals, adding context and emotion, and guiding the audience to action. Data storytelling can be applied to various formats, such as presentations, reports, articles, videos, podcasts, and more. It can also be combined with interactive dashboards to create immersive and interactive data stories.

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Janet Gehrmann

Co-founder, Scoop Analytics | Simplifying weekly reporting for GTM leaders
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Story telling is key to making your audience understand the why behind the data (think of a Ted talk!). Some tips for data storying include: Narrative Flow: Structure your data storytelling like a narrative with a clear beginning, middle, and end. Introduce context and background, present key findings logically, and conclude with insights or recommendations. Engage with Visuals: Use compelling visuals such as charts, graphs, and maps. Visuals should be easy to interpret and directly related to the story you're telling. Humanize the Data: Connect data to real-world examples or anecdotes to make it relatable. Use storytelling techniques like anecdotes, case studies, or quotes to illustrate the impact of the data.

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Dilean Molina

OpEx, CX, Reporting & Data Analytics, Process & Resource Optimization, Strategic Planning
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If you want to delve deeper into this subject, I highly recommend reading "Storytelling With Data" by Cole Nussbaumer Knaflic. This book covers a wide range of topics, including the interaction between the human brain and data visuals, as well as providing practical tips for enhancing the readability of your data visuals.

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3 Data visualization

Data visualization is a practice of using graphical elements to represent data in a visual way. It can help reveal patterns, trends, outliers, and relationships in data that might otherwise be hidden or overlooked, as well as make data more accessible, understandable, and memorable for the audience. Data visualization is constantly evolving with new techniques, tools, and formats emerging every day. For example, augmented reality (AR) and virtual reality (VR) can create immersive and interactive environments where data can be visualized in 3D and manipulated with gestures or voice commands. Additionally, artificial intelligence (AI) and machine learning (ML) can automate and enhance data visualization processes. Finally, data art and generative design approaches can use data as a source of inspiration to produce aesthetic and artistic visualizations that evoke emotions and meanings.

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Janet Gehrmann

Co-founder, Scoop Analytics | Simplifying weekly reporting for GTM leaders
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Some best practices for data visualization include: Clarity and Simplicity: Keep visualizations clear and simple to avoid confusion. Use straightforward labels, titles, and a consistent color scheme. Relevance and Context: Ensure your visualization is relevant to the audience and provides meaningful context. Use annotations or captions to explain key points. Choose the Right Type: Select the appropriate type of visualization (e.g., bar chart, line graph) that best represents your data and supports your message effectively.

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4 Data literacy

Data literacy is the ability to read, comprehend, evaluate, and communicate data. It is an essential skill for anyone who wants to present data competently and confidently. Data literacy can help you ask the right questions and define the purpose of your data presentation, source reliable data, apply suitable methods and tools to analyze and visualize data, interpret and explain data insights and findings, tailor your data presentation to your audience, and address ethical and social issues related to data use. Furthermore, it is not only a technical skill but also a cultural and behavioral one that requires curiosity, critical thinking, collaboration, and ongoing learning. To improve your data literacy, you can take online courses, read books and blogs, join communities and events, and practice with real-world datasets.

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5 Data ethics

Data ethics is the branch of ethics that deals with the moral implications of data collection, analysis, use, and presentation. In the age of big data, where data is abundant, diverse, and powerful, data ethics has become increasingly important. It can help to respect the privacy and rights of those involved, ensure accuracy and validity of data, avoid bias or discrimination in data presentation, promote transparency and trust in data usage, and align data goals with societal values. Data ethics is not only a legal or regulatory concern but also a moral and professional one; it requires responsibility, integrity, and empathy. To enhance data ethics, one can follow codes and guidelines, consult experts and peers, seek feedback and consent, and reflect on the impact of their actions.

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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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What are the latest trends and innovations in data presentation and how do you keep up with them?

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1 Interactive dashboards

2 Data storytelling

3 Data visualization

4 Data literacy

5 Data ethics

6 Here’s what else to consider

Data Presentation

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