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Designing Immersive Data-driven Experiences

The blog discusses the importance of effective data visualization in improving communication, decision-making, engagement and collaboration, understanding of data, and saving time.
 
10 minutes read
Rakesh Nagpal

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Rakesh Nagpal
Practice Director, Data Storytelling & BI Product Design Solutions
10 minutes read
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As an avid believer of how a good design can have a positive impact and influence on the business and its users, I strongly advocate setting intuitive and engaging experience design standards across reporting tools, technologies, technical constraints and project phases. This is facilitated through a unique medium of "Art + Technology" with a design philosophy of… Maximizing Insights and Minimizing Clicks

Visual communication is one of the most powerful tools of innovation to communicate a story for a specific brand, product or a use case in an engaging, visually appealing and creative ways. As one of the very famous quote states… “Image speaks a thousand words”, this has been the personal mantra to help enterprises to tell a visual story with data, across BI Technologies, with an ease of usability and persona driven by understanding organization’s brand values and by understanding the way various business users interact with their day-to-day reports, dashboards and setting best-in-class, interesting data-driven experience standards, across tools and technologies, using best practices, design thinking and HCI (Human Computer Interaction) methodologies.

The most important benefits of effective Data Visualization

  1. Improved communication: It can help you communicate your findings to others more effectively. When data is presented visually, it is easier to understand and interpret. This can help you get your point across more clearly and concisely
  2. Better decision-making: It can help you make better decisions by providing you with a clear and concise overview of your data. When you can see the data briefly, you can identify trends and patterns that would be difficult to spot in a table or spreadsheet. This can help you make more informed decisions about your business or project
  3. Increased engagement and collaboration: It can help you engage and collaborate with your audience and keep them interested in your data. When data is presented in a visually appealing way, it is more likely to capture people's attention and hold their interest. This can help you get your message across more effectively and build stronger relationships with your audience
  4. Enhanced understanding: It can help you understand your data better by making it easier to see patterns and trends. When you can see the data briefly, you can get a better understanding of what it means and how it relates to your business or project. This can help you make better decisions and improve your results.
  5. Saved time: It can save you time by helping you find the information you need more quickly. When data is presented visually, it is easier to scan and find the information you are looking for. This can save you time searching through tables and spreadsheets.

Data visualization is a powerful tool that can be used to communicate complex information in a clear and concise way. Data visualization can be used to identify trends, patterns and outliers in data. It can also be used to tell stories and make data more engaging.

While crafting or strategizing on building data visualization solutions, it is important to keep the audience and user persona in mind. The visualization should be easy to understand and should communicate the message through data. The three main aspects for setting highly successful and engaging experiences, are crafted around… Data SEA – building Simple, Engaging, Actionable, by firstly, understanding the data aspect (KPI’s / metrics to be visualized), which ‘enlightens’ to set ‘engaging’ visual experiences, which are highly intuitive and ‘self-explanatory’ for the end users with a ‘narrative’ approach, and the convergence of these three points is the true ‘Power of Storytelling’ (as illustrated below…)

power-of-storytelling

Turn Data into Opportunity
Drive better business decisions across organization, with engaging and storytelling data visualization experiences.

The three key aspects and tenets of immersive data-driven experiences – “Data SEA

data-driven-experiences

Simple
Building simple data visualization experiences is a great way to communicate your data in a clear and concise way. By following a few simple steps, you can create visualizations that are both informative and engaging.

  1. Keeping audience in mind to design the right data-driven experience
  2. Choosing the right type of visualization for the dataset
  3. Using clear and concise content labels
  4. Applying the right set of branded colors and consistent typography (fonts)
  5. Testing the on-tool visualization filters and user flows

Engaging
While setting the initial design strategy and crafting the overall data visualization experience flow (conceptually), the important aspects have been structured with these proven and guided approach, either it’s for an Executive, with action-based insights guiding executive users from highly summarized views to one-level down details views, or for an Analyst level users, to have more detailed tabular data with options to further analyze to discover their data insights in minimal clicks.

  1. Personalized and Branded Experience – adopt and set organization brand standards, color palette, typography, responsive design approach (as needed)
  2. Summarized View – with highlighted and actionable executive insights
  3. Detailed View – with expanded metrics for detailed analysis on a chosen KPI
  4. Guided and Intuitive Experience Approach – engineering the right hover-over insights and drill-down user flows

Actionable
Building actionable data visualization experiences is a process of creating visualizations that are not only informative but also enable users to act. This can be done by designing visualizations that are easy to understand, provide clear insights, and allow users to interact with the data in meaningful ways.

There are a number of factors to consider when building actionable data visualizations. First, it is important to choose the right type of visualization for the data you are trying to communicate. Different types of visualizations are better suited for different types of data, so it is important to select the one that will best allow users to understand the information.

Second, it is important to make sure that your visualizations are easy to understand. This means using clear and concise labels, avoiding clutter, and using colors and typography (fonts) that are easy to see. It is also important to make sure that your visualizations are visually appealing, as this will make them more likely to be noticed and engaged with.

Third, it is important to provide clear insights in your visualizations. This means using the data to tell a story or to highlight important trends or patterns. It is also important to make sure that your data visualizations are actionable, meaning that they allow users to take some kind of action based on the information they are presented with.

Finally, it is important to allow users to interact with your visualizations in meaningful ways. This could involve allowing them to filter the data, zoom in and out, or drill down into specific details. By allowing users to interact with your visualizations, you can make them more engaging and informative.

 

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Data visualization merges art and science to simplify complex data for actionable insights. It's a branch of stats and theory development, using engaging forms to represent information effectively.

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Data Visualization is both an art and science. It is viewed as a branch of descriptive statistics by some, but also as a grounded theory development tool by others. Data Visualization is about being simple and representing data effectively in engaging forms for actionable insights.

The future of data visualization is likely to be shaped by advancements in technology such as virtual and augmented reality, machine learning, and artificial intelligence. These technologies are expected to make data visualization more interactive, immersive and provide more insightful analysis. Additionally, the increasing volume of data generated across various industries and the need for faster and more effective decision making will drive the demand for innovative data visualization solutions. In conclusion, the future of data visualization will be characterized by more intuitive, automated, and engaging visualization tools that provide deeper insights into data.

“Creativity is the act of turning new and imaginative ideas into reality. Creativity involves two processes: thinking, then producing.”

Creativity is intelligence having fun!
– Albert Einstein

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