5 Disadvantages of Excel for Data Visualization

Spreadsheets have become the de facto tool for data storage and analysis. With Microsoft's productivity services reaching 1.1 billion users worldwide, Microsoft Excel potentially commands an unprecedented user base that could approach the billion-user mark. The rise of Excel makes sense, it’s a powerful program that most business people interact with every week to crunch numbers and visualize data. In fact, industry statistics show that more than one in eight people globally rely on these productivity tools, highlighting Excel’s enduring appeal as a flexible and user-friendly solution for data analysis.

The ease and flexibility of Excel often make it a first stop for creating data visualizations, but that doesn’t make it the best tool for data visualization. Like everything else, it has disadvantages. Excel is first and foremost a spreadsheet tool, and while it does have some data visualization capabilities, they are very limited compared to modern data visualization software, like Sigma.

Cloud-based analytics solutions make it easier to quickly build out data visualizations, create business dashboards that automatically track organization KPIs, and drill down and explore data on a granular level.

If you use Excel to make data visualizations, you’re not alone. But here are five disadvantages of data visualization in Excel to help you reconsider using it in your daily workflows and switch to a more comprehensive cloud-based analytics solution like Sigma.

1. Excel makes unstructured data a challenge

A major disadvantage of Excel is the challenge of analyzing real-time unstructured and semi-structured data in it. Conversely, many new and upcoming data analytics tools can quickly recognize this type of data and create visualizations.

Excel also flounders when it comes to data formats such as JSON. The proliferation of mobile data, apps, and IoT devices has made JSON the fastest-growing type of data. Yet, its complex structure poses a challenge for even the most experienced users of Excel. However, modern analytics platforms, such as those with advanced text processing, enable users to unravel and analyze such data in an Excel-like environment in seconds.

Conquering complex data streams

Modern Business Intelligence (BI) platforms smoothly process diverse data types, breaking through traditional spreadsheet limitations. For example, a global e-commerce company demonstrates this capability by integrating complex data streams, web logs in JSON format, customer interaction data in XML, and transactional records, into unified visualizations. 

By connecting directly to cloud data warehouses, these platforms automatically prepare data, revealing insights that would remain hidden in Excel, and allowing instant analysis of intricate, nested data structures that would typically require weeks of manual compilation.

2. Excel can’t design interactive dashboards

A data visualization tool allows you to combine several types of charts to create interactive dashboards that display all of your KPIs in one place. Then, you can dig deeper into each chart, exploring its granularity and investigating trends.

You can create dashboards in Excel, but they are static, showing only high-level trends, and serving as a conclusion rather than a starting point for further exploration. This is a disadvantage when compared to dynamic dashboards which can automatically update.

Interactive dashboards, on the other hand, allow you to drill down and answer follow-up questions raised when you see a trend in your visualizations. These dynamic insights act as a launchpad, propelling teams toward deeper questions, smarter decisions, and closer collaborations.

Drilling down: A marketing perspective

A marketing team can illustrate the impact of interactive dashboards by creating a dashboard that allows instant drilling down from high-level metrics to granular details. 

With a single click on a total revenue chart, users can break down performance by region, product line, or individual sales representative, dynamically adjusting views and exploring hypothetical scenarios. This changes data into a tool that actively helps you, unlike Excel's static reports.

3. Excel doesn’t update in real-time

Data kept in Excel spreadsheets are stale. The moment you import a CSV file and build out a worksheet, data becomes out of date because it doesn’t connect to a live data warehouse. This forces users to suffer through manual processes to report the same information over and over again.

While Excel is capable of connecting to external data sources via plugins, a cloud-based data visualization tool can smoothly connect to dozens of data sources via a cloud data warehouse like Snowflake. This allows for immediate access to up-to-date data, simplified visualizations, easy sharing across your organization, and the ability to make faster, more informed business decisions.

Breaking the staleness barrier

Real-time data analysis has become essential for organizations needing to make quick, informed decisions. A financial trading firm exemplifies this approach, using a BI platform that continuously pulls live market data, updating dashboards in milliseconds. 

Traders can view real-time currency exchange rates, stock prices, and market trends without manual refreshes, allowing immediate strategic decisions. This dynamic approach contrasts sharply with Excel, where data becomes obsolete the moment it's imported, potentially leading to missed opportunities and uninformed choices.

Still have questions? Learn more about the value of real-time data analytics.

4. Excel doesn’t foster collaboration

Excel workbooks are primarily stored locally, and while cloud access exists, its collaboration features are limited to individual worksheets. This results in endless duplication of efforts and creates a mess from an organization's perspective when someone wants to build off of another person’s work.

Conducting analyses in a vacuum is a poor use of time. Excel makes it difficult for teams to share, collaborate, and discover answers efficiently and can consequently put companies at a disadvantage.

With a data visualization tool, teams can break down data silos, easily collaborate and elevate each other’s work. This is how you build compound interest with data: start by extracting insights from the base data, then build upon those findings.

Global insights, shared workspace

Modern data platforms transform collaboration from an individual task to a team-driven process, breaking down traditional barriers to shared insights. A global consulting firm demonstrates this by using a BI platform that allows analysts around the world to simultaneously work on the same dashboard. 

Data scientists and business analysts can contribute in real-time, with the platform tracking changes, maintaining version history, and ensuring sensitive data remains accessible only to authorized team members. This collaborative analysis creates a rich, dynamic analytical process that goes far beyond Excel's limited sharing capabilities.

5. Spreadsheet sprawl is a security risk

Downloading data to a spreadsheet and storing it locally is dangerous. Unlike BI tools, Excel spreadsheets don’t require specialized SQL coding expertise, which is why so many business users continue to use it, despite the risks. 

Unfortunately, the risks are plentiful and so are the disadvantages it brings. When data is downloaded to Excel, the data team loses visibility into how employees use or share the data, resulting in a lack of security and compliance oversight. This leads to vulnerabilities, lost data, and misuse.

Compliance in the cloud

Modern BI platforms offer comprehensive data security, addressing a pressing business need that traditional spreadsheets cannot match. A healthcare organization illustrates this approach by implementing a centralized platform that eliminates the risk of sensitive patient data being downloaded to individual spreadsheets. Instead, all data remains in a secure, cloud-based environment with granular access controls, where junior analysts can view aggregated statistics while senior researchers access more detailed information, all without downloading a single file. Automated compliance tracking creates an auditable trail that protects both the organization and individual privacy.

Even Microsoft suggests “moving sensitive information and systems to a cloud provider” rather than storing it on a personal computer to prevent security breaches. Opt for a data solution that provides answers to important business questions without removing data from the data warehouse or downloading it to a PC.

Move past Excel's visualization limits

For complex organizations with modern data analytics programs that want to achieve beautiful, yet useful data visualizations quickly, Excel simply won’t do. Make the switch to a solution that offers a familiar spreadsheet experience backed by the full power of SQL and the cloud data warehouse.

Sigma is always adding new types of visualizations to our tool. To see which of these are currently supported, visit our help center.

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