At present, data visualization holds immense value within any successful organization. It should not be underestimated.
Effective visual representations of data sets and statistics allow business leaders and teams to make educated decisions, identify opportunities, and stay ahead of their competition.
Microsoft Excel has long been recognized for its reliable data visualization features. However, Excel may not work as effectively when working with large datasets.
This article explores why more powerful and specialized tools are necessary for data visualization and compares Excel's shortcomings with better alternatives for modern business decision-making.
Limitations of Excel for Data Visualization
Excel is an established application for producing simple visual displays like pie charts, bar charts, line graphs, and graphs.
However, it has significant limitations and challenges, such as:
- Lack of advanced visualization options like interactive dashboards, heatmaps, and tree maps.
- Inability to combine multiple chart types into a single visualization.
- Lack of interactivity features like hovering over data points or filtering data based on specific criteria.
- Excel was never intended to handle large data sets effectively, and users may struggle with analyzing thousands of rows effectively.
- Limitations in its ability to manipulate data beyond simple filtering and sorting.
- Processing and calculation time limitations and leading to errors in the visualizations.
- Creating dynamic visualizations in Excel can be challenging due to the software's inability to handle complex datasets.
- Excel doesn’t allow for any intuitive, drill down type functionality as well
Beyond these limitations, there are numerous other challenges that users must know.
Challenges of Working With Excel
Excel can present one of its greatest obstacles when cleaning and transforming data within its program.
When working with data in Excel, common challenges include:
- Formatting inconsistencies
- Formatting missing or incorrect data points
- Formatting duplicate entries
- Limited capabilities
- Lacking the ability to integrate with external data sources
These shortcomings have led to the rise of specialized data visualization tools as an emerging alternative to Excel's limitations.
The seamless integration of these tools with various data sources and formats ensures that users can efficiently integrate external data sources and create interactive visualizations to extract meaningful insights from their data.
Key Advantages of Specialized Tools over Excel
Specialized tools like Explo offer a range of advantages for data visualization over Microsoft Excel.
A diverse range of visualization options
With Explo, users can choose from various chart types and easily customize them with a few clicks, creating more engaging and informative visualizations that tell a cohesive story from complex datasets.
Seamless integration with various data sources and formats
This flexibility helps maximize efficiency in extracting insights from their data for greater insights from analyses.
Enhanced performance and scalability
Explo is designed to handle the diverse and complex data sets commonly required for business intelligence and analytics.
With enhanced performance and scalability, users can efficiently manipulate and analyze their data without worrying about sluggish performance or lag time.
Advanced data exploration and interactive features
Explo has a drag-and-drop interface. Users can quickly filter, sort, and group their data, enabling them to explore different insights and patterns.
Explo enables users to build interactive dashboards allowing real-time data visualization analysis for an engaging and insightful visualization experience.
Real-World Examples: Excel vs. Embedded Analytics
Microsoft Excel has long been considered an indispensable data analysis and visualization platform. However, Excel is far from ideal when it comes to more advanced data visualization techniques.
Here are some examples that demonstrate the limitations of Excel and how specialized tools like embedded analytics can offer more capabilities.
- Business analysts can boost their efficiency by using data visualization tools with embedded analytics. Unlike Excel, these tools provide intuitive interfaces that allow users to refine and cleanse data effortlessly, ensuring timely and accurate results.
- Excel has limited visualization options compared to specialized analytics tools. For instance, Excel does not support advanced data exploration, visualization, or responsive charts. In contrast, embedded analytics offers various chart types, interactive visuals, and powerful data manipulation tools that allow users to create more engaging visualizations.
- Embedded analytics provides built-in data refining and cleansing tools not available in Excel. These capabilities enable users to transform data that is dirty or from different sources into a consistent and clean format, ensuring accurate and timely results.
- Excel is primarily a desktop-based tool, making it difficult for teams to collaborate or share data insights. In contrast, embedded analytics tools provide online access to data, enabling multiple users to collaborate and share analyses in real time.
- Embedded analytics tools like Explo allow for a wide range of chart options, including heat maps, geo-mapping, funnels, dynamic scatterplots, and more.
Embedded analytics programs are intuitively designed for visual appeal and interactivity and have built-in tools to assist with countless operations for a customized user experience specific to your business needs.
Data visualization requires careful thought to accurately display information in an easy and digestible form for all. Excel alone is not enough, and by only using Excel as a tool for presenting information, you risk different stakeholders confusing or misinterpreting results.
The benefits of using an intuitive reporting and analytics solution (like Explo) can provide users with a diverse range of visualization options and reports for better insights.
Try Explo for yourself and see how easy it is to get started with data visualization.