10 data visualization trends to watch for in 2023 and beyond

Data visualization has become indispensable for analyzing and communicating data in the modern digital era. As data volumes grow exponentially, visualization provides a more efficient way to explore, understand, and present complex datasets. Data visualizations utilize the power of human visual perception to identify patterns, relationships and insights that might otherwise remain hidden in rows of numbers and text.

Looking ahead, we can expect data visualisation to be more prominent in supporting data-driven industry decision-making. Here are key trends that will shape the world of data viz in 2023 and beyond:

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1 The rise of interactive data visualizations

Static charts and graphs are no longer enough. Interactive data visualizations allow users to drill down into the data, highlight specific points, filter different variables, and customize the view for deeper exploration. Interactive capabilities turn data exploration into an engaging hands-on analytics activity. Dashboards with cross-filters give business analysts superpowers to slice data on the fly for rapid insights. These rich capabilities make interactivity a must-have for leading visualization tools.

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2 Augmented and virtual reality will enhance data immersion

By overlaying data visualizations onto real-world environments, augmented reality (AR) and virtual reality (VR) will take data immersion to a new level. Imagine walking through a manufacturing plant and having real-time data on equipment performance pop up before your eyes, or viewing 3D data structures and manipulating them with your hands. Forward-looking companies like General Motors use AR to visualize assembly line data and optimize workflows. The spatial dimension of AR/VR provides a natural match for exploring complex informational spaces.

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3 More focus on automated insights and intelligent analysis

Artificial intelligence will increasingly power data visualisation, assisting with automated analysis. Machine learning algorithms can now process massive datasets to highlight critical data points, detect anomalies and patterns, forecast trends, and generate insights faster than humans. AutoML tools make complex analytical workflows accessible to citizen data scientists. Expect more innovative recommendation engines to suggest optimal graph types based on the data structure. Advances in natural language generation will help turn visual data discoveries into automated narrative reports .

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4 Data storytelling will become more prominent

Data storytelling, which presents critical data insights in an engaging narrative flow tailored to a specific audience, is going mainstream. Storytelling approaches make data more memorable and impactful. Leading companies are building in-house data journalism teams to unearth compelling stories from their data. Data artists are creating innovative data comics, zines and physical installations as creative storytelling formats. Data storytelling will be a crucial skill to develop to make analytics relevant across the organisation.

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5 Democratization of data analysis

Self-service analytics and no-code tools are democratizing access to data exploration beyond technical specialists. More employees can now create their own interactive dashboards relevant to their workflow using drag-and-drop interfaces. Natural language interfaces allow asking questions of data conversationally in plain English to get customized visualizations. Collaborative features support data sharing and embedding for decentralized analytics. Democratization will spread data literacy and a culture of data-driven decision-making across teams.

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6 Focus on streaming and real-time data

The ability to analyze real-time and streaming data unlocks immense value, from detecting cyber threats to monitoring supply chain disruptions to leveraging insights for just-in-time decisions. New techniques focus visualization on displaying what is happening across fast-changing data. Real-time dashboards will increasingly become operations centres for time-sensitive domains like network ops, transportation, e-commerce and IoT. Support for streaming data inputs will allow sharper predictive algorithms to boost forecast accuracy.

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7 Data visualization applications will diversify

While business analytics has been the traditional stronghold, data visualization will continue expanding into diverse disciplines. Data journalism has brought increased transparency by visualizing patterns in public datasets. More data artists are using creative visualization for social commentary. Visualization plays a growing role in science education, healthcare communication, policy advocacy and data activism. Expect more startups to apply dataviz to help everyday users track their data from health, finance, productivity and social media.

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8 Multi-modal approaches will provide unique perspectives

No single visualization can capture every data insight from every angle. Combining multiple graphs, charts, maps, animations, and illustrations provides a richer perspective. Linked multi-modal views allow toggling between different visual metaphors for the same dataset. Animated transitions animate changes between states. Hybrid visualization blends charts with graphical abstractions like node-link diagrams. The synergy of multiple visualization types will enable more holistic data exploration.

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9 Ethical considerations will be front and centre

Like any technology, data visualization can be misused if poorly designed or implemented without care. Ethical considerations will receive greater attention to avoid issues like misleading designs, biased assumptions, privacy violations and improper interpretations. Responsible dataviz follows principles like showing data transparency, accounting for uncertainty, maintaining context and considering diverse perspectives. Dedicated data ethicists can help guide organizations in upholding ethics.

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10 Ubiquitous deployment on more platforms and devices

Data visualizations are breaking free of desktop screens to be viewable on the platforms where users spend their time. Dashboards optimized for mobile phones and tablets support on-the-go decision-making. Data-driven apps put tiny data graphics at your fingertips. Omnichannel publishing means creating visualizations once for seamless web, mobile and print access. Connected TVs and intelligent assistants like Alexa enable ambient data displays . Embedding and sharing expand dataviz reach. The ubiquity of dataviz promotes pervasive intelligence.

In summary, data visualization is entering an era of unprecedented innovation and expanded impact across industries. To stay competitive, organizations must actively monitor developments on the data visualization front and be ready to adopt the most valuable advancements. With the right strategies, data visualization can become a true force multiplier for leveraging data as a core business asset and driving transformative outcomes.

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About the author

My name is Andy Pemberton. I am an expert in?data visualization . I guide global clients such as?Lombard Odier , the?European Commission ?and?Cisco ?on the best way to use data visualization and then produce it for them: reports,?infographics ?and motion graphics. If you need your data visualized contact me at [email protected] or call 07963 020 103

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