Overall Satisfaction with Microsoft Excel
I use Microsoft Excel daily in my organization as a Research and Development Consultant. Currently, it's our main software for data entry, analysis, graphing, and just general tracking of participants. Therefore, I use it for pretty much everything. For more complex analyses, we do use the Statistical Package for the Social Sciences (SPSS).
- Conditional formatting of cells using regular rules.
- Filtering of cells.
- Quickly summarizing data.
- Calling data from other spreadsheets into formulas.
- Counting conditionally formatted cells (e.g., you have 5 green cells, 10 red ones, and 3 orange ones in a row).
- Merging cells in a table; I have to remove the table first and then re-add the table to merge cells together.
- Offering more preset colour categories for formatting graphs.
- Built-in functions to run ANOVAs, Multiple Linear Regression, Factor Analysis, etc.
- Allows us to quickly glean insights from data for clients in a time-sensitive manner.
- Widely accessible to others in the organization, promoting knowledge sharing and quick feedback from colleagues.
- Relatively easy-to-use, promoting time saving within data analysis work.
- A negative is that it's quite difficult to merge many data extractions together into one single Master Data file. It requires Power Query and has bugs associated with using this.
Out of Microsoft Excel, Microsoft Power BI, IBM SPSS, and Google Sheets, Microsoft Excel is by far the most common tool used for anything data-related across organizations. Accordingly, our organization has also implemented Microsoft Excel as a first-step tool. We recently adopted Microsoft Power BI (the free version), and use it occasionally (mostly for creating dashboards), but it is less commonly understood by stakeholders across our organization and by our clients. Accordingly, Microsoft Excel is more user-friendly and because of its popularity, we can easily look up how to do things in the program online. Google Sheets is a comparable alternative to Microsoft Excel, but because it's cloud-based and we have sensitive data that needs to be protected, we chose against using this software. Finally, a few users (including myself) have access to and utilize IBM's SPSS. For my role, it's a helpful tool to do more rigorous analyses. However, because of its cost and limited functionality as a simple spreadsheet, we only use it for more complex analyses.
Do you think Microsoft Excel delivers good value for the price?
Are you happy with Microsoft Excel's feature set?
Did Microsoft Excel live up to sales and marketing promises?
Did implementation of Microsoft Excel go as expected?
Would you buy Microsoft Excel again?
From my experience, Microsoft Excel is well-suited for storing data we gather from participants, cleaning the data, tracking key metrics, and basic descriptive analyses. It's less suited for complex analyses such as for ANOVA, MANOVA, Factor Analysis, Multiple Linear Regression, and other more complicated statistical analyses. Additionally, it isn't the most user-friendly for building dashboards or complex visuals. For complex analyses, I recommend SPSS and for the latter, I recommend Power BI.