Data visualizations aim to represent data in highly visual, easy-to-understand ways. There are two types of data visualizations: interactive and non-interactive. What sets them apart is an option for the end user to engage with the visualization’s data.
Non-interactive data visualizations are static and simple, such as pie or bar charts. They are easy to build but don’t offer the end user ways to engage with the data.
Interactive data visualizations, on the other hand, require user engagement, such as clicking a button or moving a slider. These engaging features allow you to dive deeper into the data and answer specific queries.
Let’s take a look at the features and use cases of each visualization type.
Non-interactive Data Visualization
- Static and simple
- Quick and easy to build
- Suitable for less complex data stories
- Optimal format for printing and sharing reports via email
Interactive Data Visualization
Interactive data visualizations are highly engaging. Rather than remaining static, they offer various features that allow you to further explore large amounts of data and easily find information. With interactive visualizations, you can:
Filter your data and then hover to reveal exact information.
Zoom in for a closer look or drill in for additional information.
Pull data using conversational language with natural language query (NLQ)
- Zooming allows you to view a specific detail of the visualization without needing to create a new insight.
- Drilling allows you to move from one visualization to another, such as a different dashboard or insight. It also allows you to send an action from the dashboard (e.g., drill into another website).
- Filtering allows you to reduce or specify the data that is displayed in the visualization.
- Ideal for working with large amounts of data
- Helpful for when you have a longer list of questions or trends to investigate
- Often used in dashboards and business intelligence reports
Boost engagement and productivity. Interactive data visualizations allow and encourage users to engage with data in more productive ways. With the flexibility to adjust the visualization according to their needs, users become active participants rather than viewers alone and can get the most out of their data.
Simplify complex data. Interactive visualizations represent complex data stories clearly, making the data easier to understand and manage. By providing users with greater control over the data they work with, they can help users to easily identify trends and develop insights that lead to data-driven decisions.
Explore your data with custom-built applications. Interactivity isn’t limited to dashboards and visualizations; it can also apply to building applications on top of data. One example is NLQ, which allows you to search for information in conversational language. It creates a visualization based on your request, allowing you to quickly and easily answer specific questions.
Which Option is Right for You?
If your team is looking to answer simple data queries, non-interactive data visualizations may be sufficient for your use case. However, if your use case requires you to investigate trends with a large amount of data, interactive visualizations will better suit your needs. From interactive visualizations to NLQ, with GoodData you can work with predefined interactive dashboards or create your own interactive application and manage your analytics as code. To get started, request a demo today!
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