Many feel Tableau and Excel are competing solutions. Others think the tools are like apples and oranges.
Both tools are used for data analysis. However, each takes a different approach to exploring data and finding key insights.
Here’s a deeper look into what makes the two different:
Spreadsheet vs Data Visualization
The simple explanation: Excel is a spreadsheet tool, while Tableau is a data visualization one.
Spreadsheet tools are electronic worksheets that display data in a tabular format (a table of columns and rows). Each data point is stored in “cells” and can be manipulated by manually set formulas. Graphs, charts or presentations can be created afterward to highlight a particular insight.
Data visualization tools format data in a pictorial or graphical view to easily spot patterns, trends or correlations between data points. These tools typically connect to third-party tools to pull data and have user-friendly functionality, like drag-and-drop features or drop down menus, so users can explore data freely.
Both are able to conduct data analysis, but each tool takes a different path to get to the critical insights.
When it comes to Excel and Tableau specifically, there are three other core differences to consider:
1.) Data Discovery
Finding key insights in data helps organizations remain competitive within their markets. The ability to explore data and find insights is where Excel and Tableau differ greatly.
When working with Excel, you must already have an idea of where the data needs to lead you to find critical insights. As Bridget Cogley puts it in her guide to Tableau, you have to answer The Question. Since Excel saves data in a tabular format, this means your path to an insight involves mapping out your answer, building formulas and visualizations, and analyzing the information.
However, Tableau allows you to freely explore data without knowing the answer you want ahead of time. With drill-down and data blending features built in, you’re able to spot correlations and trends, and then dig down to understand what caused them to happen, rather than the other way around.
2.) Manual vs Automatic
Many organizations rely on up-to-date data to make critical decisions.
Excel is a static tool. In order to update or refresh the worksheet, you must manually plug in data. And to automate repetitive tasks you have to create macros, which requires VBA (Visual Basic for Applications) knowledge. Making macros tends to be time consuming, but can save time in the long run.
Tableau, however, automatically updates information in real-time into its system, so refreshing data and views is a simple. Even if creating calculations in a tabular format, the formula is typed once, stored as a field and applied to all rows within that source.
Visualizations are a great way to highlight the data that’s important.
In Excel, you first manipulate the data on the cell level, and then manually create visualizations like graphs, charts, PowerPoint presentations, etc. To simplify visualization creation, you need a deep understanding of how Excel’s features work.
Tableau visualizes data from the start, allowing you to see the significance right away. Tableau differentiates correlations using color, size, labels and shapes, giving you context as you drill down and explore on a granular level.
Making the Switch
Even as a static tool, Excel is still the most commonly used data analysis solution for businesses because there is value in storing and manipulating data in a spreadsheet.
Tableau has realized this value and can connect to Excel as a data source. This allows you to use the two solutions hand-in-hand for greater analysis.
With that in mind, there are a few telltale signs you need to supplement Excel with Tableau, or completely switch all together. Here are two of the most significant:
- Your business needs to pull data from numerous sources.
- Exporting all your Excel worksheets has become too slow and cumbersome, eating up precious company time.
If your company needs to make the switch from Excel to Tableau, you may encounter some end-user apprehension. As stated by Ryan Sleeper, the director of data visualization at Evolytics, some tips to overcome adoption apprehension are:
- Introduce the benefits and value of data visualization. Many times end users push back because they don’t know how a change will benefit them. Ease their minds by having information sessions or workshops to walk them through key features, address any concerns and answer all their questions.
- Show how to conditionally format rows and columns. Conditioning table views in Excel and Tableau are two different processes. In Excel, you can format each cell, but in Tableau it seems like an “all or nothing” ordeal. Make sure to tell end users how to use a Marks Card in Tableau to get the same conditioning capabilities as in Excel.
- Prepare data to be used with Tableau. Many users who are new to Tableau get frustrated when connecting to Excel spreadsheets directly. Tableau automatically interprets the data points to classify fields and set up a logical work space. This becomes frustrating when Excel spreadsheets aren’t formatted in a way that translates well into Tableau. To prevent this, set up Excel sheets vertically rather than horizontally, or by using columns instead of rows to represent unique fields.
Wondering how Tableau stacks up against other data analytics solutions? Check out some of our comparisons with top contenders in the market.