Microsoft Excel Reviews & Product Details

What I appreciate most about Microsoft Excel is its remarkable versatility and robust data analysis features. Excel enables users to handle a wide range of tasks, from basic data entry and calculations to more advanced activities like financial modeling, data visualization, and automation through the use of formulas, PivotTables, and macros. Review collected by and hosted on G2.com.

One aspect I find frustrating about Microsoft Excel is how challenging it can be to manage and maintain when dealing with large or complex datasets. For example, performance can suffer significantly—Excel may slow down or even crash when processing very large files or intricate data models. Additionally, although Excel Online and OneDrive have improved things, real-time collaboration still isn't as smooth or intuitive as what you get with tools like Google Sheets. Review collected by and hosted on G2.com.

What I like most about Microsoft Excel is its flexibility and powerful features for data handling. It makes calculations, data analysis, and reporting very easy with formulas, pivot tables, and charts. Excel is reliable, works well with large datasets, and integrates smoothly with other Microsoft tools, which helps save time and improve productivity. Review collected by and hosted on G2.com.

Sometimes Excel becomes slow when working with very large files or complex formulas. Advanced features like VBA and macros can also be difficult for beginners and require time to learn. Occasional formatting issues when importing data from other tools can be slightly frustrating. Review collected by and hosted on G2.com.

The best thing about Excel is its unmatched power for data analysis. Features like PivotTables and XLOOKUP make it incredibly easy to organize thousands of rows of data. It’s the industry standard for a reason—it can handle complex financial modeling that other spreadsheet tools just can't touch.

I love how flexible Excel is. I use it for everything from simple checklists to complex project trackers. The conditional formatting and automation help me visualize trends quickly, and since almost every business uses it, sharing files with clients is always seamless and headache-free.

Excel is a huge time-saver. Once you learn a few key formulas or set up Power Query, you can automate repetitive tasks that used to take hours. It's reliable, fast, and the integration with the rest of Microsoft 365 makes my workflow much smoother. Review collected by and hosted on G2.com.

The learning curve can be pretty steep. While basic tasks are easy, the more advanced features—like Power Pivot or complex nesting formulas—aren’t very intuitive for a beginner. You often have to spend a lot of time on YouTube or forums just to figure out how to do one specific thing.

It can get sluggish or even crash when you're working with massive datasets or too many formulas. If a file gets over 50MB, you start to see 'Not Responding' messages, which is frustrating when you're in the middle of a big project. It still feels a bit 'heavy' compared to lighter web-based tools.

Collaborating in real-time is better than it used to be, but it's still not as smooth as Google Sheets. Sometimes you get 'versioning' errors or sync conflicts when multiple people are editing a workbook at once, which can lead to data being overwritten or lost if you aren't careful. Review collected by and hosted on G2.com.

Microsoft Excel is its versatility and reliability across both industry and academic use cases. With over three years of experience in software testing and three years as a CSE researcher, I have consistently used Excel for test case management, defect tracking, data validation, and reporting, as well as for research data analysis, preprocessing, and visualization.

Excel’s powerful features such as pivot tables, advanced formulas, conditional formatting, and data validation make it extremely effective for analyzing large datasets and identifying patterns or anomalies. From a testing perspective, it helps in maintaining structured test documentation and generating clear reports for stakeholders. From a research standpoint, it serves as a quick and efficient tool for exploratory data analysis before moving to advanced tools.

Overall, Excel strikes a perfect balance between ease of use and analytical power, making it an indispensable tool for professionals across domains. Review collected by and hosted on G2.com.

One limitation of Microsoft Excel is that it can become slow and less efficient when handling very large datasets, and it lacks advanced automation and version control features compared to specialized data analysis tools. Review collected by and hosted on G2.com.

I like Microsoft Excel because it efficiently converts raw data into structured, computable formats. It performs calculations with high accuracy, supports large datasets, automates repetitive tasks through formulas and macros, and enables logical decision-making through analysis and visualization. It reduces human error and optimizes time, resources, and output. Review collected by and hosted on G2.com.

I dislike Microsoft Excel because it is highly dependent on manual input, which increases the risk of data inconsistency. Performance degrades with very large datasets, complex formulas are difficult to audit, and version control is limited in collaborative environments. Errors can propagate silently if not detected. Review collected by and hosted on G2.com.

Microsoft Excel is an excellent application where calculations and data analysis, data transformations and dashboard visualizations are done on single platform. It has robust bank for formulas and tools that are easy to use. My favorite formulas are xlookup, sumifs, countifs, Filter function, index, match, Byrow, Bycol, Tocol, torow, lambda functions and many more. It has powerful languages and scripts like VBA, Python, Power Query M Code, DAX. Review collected by and hosted on G2.com.

Excel is slow when data is large like 3 to 4 lac rows. Review collected by and hosted on G2.com.

What I like the most about Microsoft Excel is how versatile it is. You can use it for basic tasks like maintaining lists, creating schedules, or simple budgets, and also for advanced work such as formulas, pivot tables, and automation using macros. Excel makes it easy to structure data, filter values, and visualize information through charts and graphs. It is also widely used across teams, so sharing and collaborating becomes smooth without needing much explanation. Review collected by and hosted on G2.com.

The biggest challenge I find is when large files become slow or take time to load, especially when they include a lot of formulas, images, or multiple sheets. Also, some advanced functions require prior knowledge, and beginners may take time to learn them. Real-time multi-user collaboration is possible, but not always seamless like cloud-native tools. Apart from that, I don’t see major issues. Review collected by and hosted on G2.com.

Microsoft Excel remains one of the most powerful and versatile tools for both personal and professional use. What I like best about Excel is its incredible flexibility. It can handle everything from basic lists and budgets to complex financial models and analytics.

Its formula system is a major strength—functions like XLOOKUP, SUMIF, and INDEX/MATCH allow users to automate tasks and transform raw data into useful insights. Excel’s PivotTables are another standout feature, making it easy to summarize large datasets in seconds.

The software also integrates smoothly with other platforms, including CSV files, databases, and data tools like Power BI. This makes it convenient for anyone who needs to move data across systems.

Overall, Excel offers a perfect balance of power and control, giving users the freedom to build exactly what they need. It’s an essential tool that continues to get better with each update. Review collected by and hosted on G2.com.

While Microsoft Excel is a powerful and essential tool, it does come with several drawbacks that can affect the user experience. One of the main issues is that Excel doesn’t handle very large datasets well. Once a file grows too big, it can become slow, unresponsive, or prone to crashing.

Collaboration is another area where Excel can feel limited. Even with cloud features, multiple users editing the same file may encounter version conflicts or unexpected changes. It’s not as seamless as modern real-time collaboration tools.

Excel also makes it easy for errors to hide. A single incorrect formula or accidental copy-paste can lead to inaccurate results, and finding the mistake can take a long time. For new users, some of the advanced features—like PivotTables or complex formulas—can feel overwhelming.

Finally, spreadsheets can quickly become cluttered or hard to navigate without proper organization. This makes sharing or reviewing files challenging, especially in a team environment.

Despite these issues, Excel remains incredibly useful, though it’s not without its frustrations. Review collected by and hosted on G2.com.

It is a golden standard of business. Since Excel was created, it substantially substituted the role of calculators and made the life of scientists and office employees more comfortable to deliver fast and rapid data analysis. I like it, and excel became a standard of work, and it has a lower entry-level as compared to programming tools and more presentation-quality to deliver fast and reliable results. Aligned with Python libraries. Review collected by and hosted on G2.com.

I like everything in Excel. It would be great to have ready-to-use direct gateways to postgre SQL cause the average file size grows yearly. SQL connectivity could be AI assisted for proper query spelling. Office 365 copilot raws text data autofill has glitches and needs to be corrected manually. Cloud based packages of MS 365 Exel has glitch of frosing at some micro seconds and that is bothering. Review collected by and hosted on G2.com.

What I like best about MS Excel is how effortlessly it turns raw, messy data into something meaningful and usable. A few things really stand out:

Power with simplicity

You can start with basic tasks like lists and totals, and gradually move into advanced analysis—formulas, PivotTables, Power Query—without changing tools. It grows with your skill level.

Speed and efficiency

Tasks that would take hours manually—calculations, sorting, filtering, comparisons—can be done in seconds. This is especially valuable in research, finance, pharmacy data, or administrative work.

Flexibility across domains

Excel works just as well for academic research data, clinical study results, inventory management, budgeting, or simple record-keeping. Few tools are that versatile.

Strong data analysis and visualization

Charts, conditional formatting, PivotTables, and dashboards make trends and patterns obvious, which helps in decision-making and presentations.

Universal acceptance

Almost everyone knows Excel at some level. Files are easy to share, review, and reuse—important for collaboration, submissions, and reports.

In short, Excel feels like a practical problem-solver: not flashy, but incredibly reliable and powerful once you know how to use it well. Review collected by and hosted on G2.com.

What I dislike about MS Excel is that, despite its power, it has some real limitations that show up once your work becomes complex or large-scale:

Error-prone formulas

A small mistake in a formula (wrong cell reference, drag error, hidden overwrite) can silently change results. In research or financial work, this can be risky if not carefully validated.

Poor handling of very large datasets

Excel slows down or crashes with large files (hundreds of thousands to millions of rows). It’s not designed to be a true database or big-data tool.

Version and compatibility issues

Files may behave differently across versions (Windows vs Mac, older vs newer Excel), especially with advanced functions, macros, or Power Query.

Limited reproducibility

Unlike programming tools (R, Python), Excel workflows are harder to document and reproduce step-by-step, which is a drawback for academic and clinical research.

Manual dependence

Many tasks still rely on manual steps (copy-paste, drag-fill). This increases the chance of human error and makes automation less robust unless VBA or Power Automate is used.

Not ideal for collaboration

While Excel Online has improved, simultaneous editing, version control, and audit trails are still weaker compared to modern collaborative data tools.

In essence, Excel is excellent for analysis and reporting—but once accuracy, scale, automation, or reproducibility become critical, its weaknesses become more noticeable. Review collected by and hosted on G2.com.