Interactive Data Visualization: Everything You Need to Know (2024)

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The world of business must grapple with a constant stream of data and information. In this digital age, the amount of information being generated on a daily basis is constantly growing as companies continue to bring more of their operations online. In order to provide results to stakeholders and optimize operations, it’s important to analyze and aggregate all of that data.

Big data has revolutionized the world of business because it offers a more accurate means of analyzing and predicting business trends and what customers want. Data Science has become an extremely coveted field of study as all industries across the world need data scientists to analyze and interpret data to come up with data-driven solutions and strategies. However, in order to reap all of these benefits of big data, it’s essential for them to be analyzed and presented in a manner that can be understood by the relevant personnel. The inability to accurately interpret data can cost businesses 30% in lost revenue.

Data Visualization is the most effective method by which to get employees and the relevant personnel to engage with the data available. Managers who incorporate data visualizations are able to harvest 28% more information than those who don’t. However, most of the data visualization methods used currently are static in form. Using Interactive Data Visualizations offers a whole host of benefits that businesses can use to drive growth faster.

In this article, we’ll explore what Interactive Data Visualizations really are, how they are beneficial, and how they can be used.

What is Interactive Data Visualization?

Data Visualization is the process of using visual aids to give expression to big data.

A simple and static form of data visualization might include spreadsheets, however, these don’t provide the kind of insight that interactive data visualization methods can.

Interactive Data Visualization includes charts, tables, graphs, and interactive displays that the users can actively drill down into and engage with. These give you simplified aggregated access to data, allow you to compare different classes of data, and forecast trends in order to formulate intelligent strategies.

Benefits of Interactive Data Visualization

The following are some of the most important benefits of data visualization.

Time for Action

Interactive data visualization saves a lot of time in data interpretation and refines business operations. As such, more time can be devoted to innovate strategies and act out on the data presented. Live data updates can also be used to deal with situations requiring immediate attention. Furthermore, since interactive data visualizations allow the team to engage and understand the data, they can collaboratively identify problems and offer solutions.

Highlighting Patterns and Trends

Interactive data visualization helps you better understand your customers and market by looking back at past trends and patterns. Once you have identified a pattern, you can use that information to determine how to proceed with operations for the future. Patterns are almost impossible to identify through traditional static forms of data visualization like spreadsheets.

Specific Information

Users can zoom out to look at the big picture of market trends and data. They can also focus on specific issues, time periods, actions, etc., and go through their details. As such, users have the ability to take specific action by going through the specific data they need at the moment, as opposed to sifting through irrelevant data.

Direct Interaction with Data

You can directly interact with real-time data as opposed to using static graphs and tables which can only be viewed. Let’s take the example of sales for product X. A spreadsheet will only tell you that the sales for product X are rising. Maps can help you identify which areas the sales are coming from and which areas or service/product segments are under-performing. Furthermore, interactive data visualization techniques like territory mapping can help you zone into a specific region and identify its needs, thus empowering you to take corrective measures like hiring a sales individual to cover that territory. Furthermore, this level of interaction can be achieved via any gadget, even while you’re on the move.

Shareable

Our minds can process images faster than text. As such, if you map out all of the relevant data in the form of engaging graphics, it can easily be understood by people, making it more shareable to the public. Although it is important to have good governance controls over your data and visualizations to maintain proper data security.

Employees Understand their Company Better

Interactive data visualization can be used to showcase the company’s growth trajectory and annual figures without confusing or boring employees. Once employees better understand where the company stands, they are able to have a deeper insight into areas that can be improved. This allows them to act accordingly and rectify pain points. For example, effective interactive data visualization can help a company’s marketing employees determine what channels to allocate their budget towards and support their point of view regarding channel spend to the stakeholders.

How to Maximize the Utility of your Interactive Data Visualization

The following strategies can be incorporated to design engaging interactive data visualizations.

Optimizing for the End-User

Who are you presenting the data to? Is it to the manager, the consumer, the accountants, HR, or stakeholders? You need to structure your data visualization for your target audience specifically.

Tell a Story

You need to use your data visualization to tell a story. This will help add focus to your presentation and make it more actionable. What are you trying to convey through the presentation? What actions would you like your audience to take? Answering these questions will help you structure the right data visualization.

Simplicity

Visualizations work best when they are focused and concise. Don’t present information that is irrelevant to the scope of your basic “story”. Get rid of graphic elements that detract from your core thesis.

Multiple Use

Your interactive visualization should be valid for a long period so you can save time if you need to make changes in the future. In order to assert its continued relevance, you need to make sure that it can be easily updated.

Examples of Interactive Data Visualization

The following are some of the most popular and effective examples of interactive data visualization methods that you can use.

• Sankey Diagrams: These are used to explain and map the flow of data, generally used for traffic measurement, data flow between network nodes, and consumption patterns.

• Tree Ring Diagrams: These can be used to chart out the hierarchies of how data interacts in a network.

• Collapsible Tree Diagrams: You can start at an initial point and then create branches depending on various different decisions and their ultimate outcomes. It helps to visualize what the outcome for different decisions will be.

• Heat Map Diagrams: If your data relies on geographical locations, you can use these diagrams to make comparisons.

Common Uses for Interactive Data Visualization

Interactive Data Visualization can prove useful in the following situations:

• Analyzing the flow of traffic on a website along with information regarding page session duration, bounce rate, conversions, etc.

• Highlighting network configurations in IT.

• Highlighting potential outcomes for various investments.

• Tracking investments over time and making future predictions.

Conclusion

Interactive Data Visualization is the ideal method by which to display information and data to the relevant individuals. It can help you skyrocket your business’ productivity, devise strategies for growth, and take considered actions after analyzing past patterns and market trends.

Interactive Data Visualization: Everything You Need to Know (2024)

FAQs

What makes an interactive data visualization? ›

Interactive data visualization is the use of tools and processes to produce a visual representation of data which can be explored and analyzed directly within the visualization itself. This interaction can help uncover insights which lead to better, data-driven decisions.

How to answer data visualization questions? ›

Your familiarity with data visualization tools is critical. Discuss your experience with popular tools like Tableau, Power BI, or D3. js and how you used them in your projects. I have extensive experience with Tableau, using it to create dashboards that provide real-time insights.

What are the 3 rules of data visualization? ›

To recap, here are the three most effective data visualization techniques you can use to deliver presentations that people understand and remember: compare to a real object, include a visual, and give context to your numbers.

What are the steps of interactive visualization? ›

The general framework for an interactive data structure visualization project typically follows these steps: identify your desired goals, understand the challenges presented by data constraints, and design a conceptual model in which data can be quickly iterated and reviewed.

What is an example of interactive data visualization? ›

Interactive data visualizations empower users to have control over the data they view. Examples include dashboards with filters, draggable time sliders on line charts, zoomable maps and scatter plots where users can hover over data points for more detailed information.

Why is interactive visualization important? ›

Visualization tools make data more accessible and understandable, so that laypersons or semi-technical users who aren't data scientists can interpret and analyze it. Interactivity. Interactive dashboards have the functionality to allow users to click on various aspects of data displays to get more information.

What are the 5 steps in data visualization? ›

  • Step 1 — Be clear on the question. ...
  • Step 2 — Know your data and start with basic visualizations. ...
  • Step 3 — Identify messages of the visualization, and generate the most informative.
  • Step 4 — Choose the right chart type. ...
  • Step 5 — Use color, size, scale, shapes and labels to direct attention to the key.

How do I become good at data visualization? ›

For more tips, read 10 Best Practices for Effective Dashboards.
  1. Choose the right charts and graphs for the job. ...
  2. Use predictable patterns for layouts. ...
  3. Tell data stories quickly with clear color cues. ...
  4. Incorporate contextual clues with shapes and designs. ...
  5. Strategically use size to visualize values.

What are the five data visualization techniques? ›

There are several common techniques used for data visualization: charts (bar, line, pie, etc.), plots (scatter, bubble, box, etc.), maps (heatmaps, dot distribution maps, cartograms, etc.), diagrams and matrices. What data visualization tools and platforms are available in the market?

What are the 4 pillars of data visualization? ›

The foundation of data visualization is built upon four pillars: distribution, relationship, comparison, and composition.

What is the golden rule of data visualization? ›

Know your story, know your audience, know your data and choose the best medium to effectively and efficiently communicate your idea in the simplest possible form. Mast these 4 golden rules and you master the art of data visualization PowerPoint creation.

What are the 7 stages of data visualization? ›

  • 1 6.
  • Step 1: Define a clear purpose.
  • Step 2: Know your audience.
  • Step 3: Keep visualizations simple.
  • Step 4: Choose the right visual.
  • Step 5: Make sure your visualizations are inclusive.
  • Step 6: Provide context.
  • Step 7: Make it actionable.

How to make an interactive data? ›

  1. Step 1: Identify Desired Goals. What is it you are trying to achieve? ...
  2. Step 2: Understand Data Constraints. ...
  3. Step 3: Design Conceptual Model. ...
  4. Step 4: Source & Model Data. ...
  5. Step 5: Design the User Interface. ...
  6. Step 6: Build Core Technology. ...
  7. Step 7: User Test and Refine. ...
  8. Step 8: Launch to Targeted Audiences.
Nov 29, 2017

What is the difference between static and interactive data visualization? ›

2 Types of Data Visualization

Static visualization refers to a method of displaying data that tells focuses on only a single data relationship. Interactive visualization allow users to select specific data points in order to present findings and create customized visual stories to compare against each other.

What is an interactive dataset? ›

The INTERACTION dataset contains naturalistic motions of various traffic participants in a variety of highly interactive driving scenarios from different countries. The dataset can serve for many behavior-related research areas, such as.

What are 4 characteristics of data visualization? ›

Accurate: The visualization should accurately represent the data and its trends. Clear: Your visualization should be easy to understand. Empowering: The reader should know what action to take after viewing your visualization. Succinct: Your message shouldn't take long to resonate.

What is an interactive data dashboard? ›

What Is An Interactive Dashboard? An interactive dashboard is a data management tool that tracks and monitors key business metrics in a centralized way. With the help of various interactive features, users can explore the data on a deeper level and make well-informed, data-driven business decisions.

What is an interactive data system? ›

An interactive data system is where information is to be added either by a health professional working on their own, or by a member of a pharmaceutical company, for example outcomes for a particular scenario.

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