Last updated on Jul 22, 2024
- All
- Business Administration
- Data Analysis
Powered by AI and the LinkedIn community
1
Pros of Excel
2
Cons of Excel
3
Alternatives to Excel
4
How to choose the best tool
Be the first to add your personal experience
5
How to improve your data analysis skills
Be the first to add your personal experience
Excel is one of the most widely used software applications for data analysis, but is it the best tool for the job? In this article, we will explore some of the pros and cons of using Excel for data analysis, and how it compares to other options.
Top experts in this article
Selected by the community from 12 contributions. Learn more
Earn a Community Top Voice badge
Add to collaborative articles to get recognized for your expertise on your profile. Learn more
- Ismael Chang Ghalimi CEO @ STOIC
16
- Qiannan Y. Machine Learning Engineer @ LinkedIn
9
- Sonia Khan BCA Graduate | Administrative Clerk | Clerical Experience in the Judicial Department | Volunteer (UK🇬🇧, Remote) |…
7
1 Pros of Excel
Excel is a popular choice for data analysis due to its ease of use and learning, with a familiar interface and a variety of functions and features. It can handle large amounts of data, up to 1 million rows and 16,000 columns per worksheet, and can perform basic and advanced calculations, such as arithmetic, statistics, logic, and financial functions. Additionally, Excel can create and customize charts, graphs, tables, and pivot tables to visualize and summarize data, and can integrate with other Microsoft products, such as Word, PowerPoint, and Outlook, as well as import and export data from various sources and formats.
Help others by sharing more (125 characters min.)
- Liz Boccolini Product Operations Manager at LinkedIn
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Excel also does not require users to learn a new language that is specific to the tool itself, unlike PowerBI and Tableau. If you want to utilize macros in Excel, then you will have to learn how to write them, but many users can do all the analysis they need without using macros.
LikeLike
Celebrate
Support
Love
Insightful
Funny
5
- Gianluca A. Trovato MBA | BEng Software Engineering | Business Development | Marketing | Online | Offline
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
I landed to this page trying to understand why Excel is not routinely recommended for analyzing common datasets. The list of cons provided alongside seems irrelevant in most real-world applications. Excel can easily and quickly handle data sets of hundreds of sizes and even larger.
LikeLike
Celebrate
Support
Love
Insightful
Funny
2
- Irakli Maisuradze Innovation Strategy Consultant | Catalyzing Business Growth
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Excel has a user-friendly visual interface that allows individuals at any level of expertise to easily learn and utilize its capabilities. Despite its ease of use, Excel is equipped with pretty robust tools that can perform complex data analysis, especially if we consider some add-ins, making it suitable for both novice and experienced professionals.
LikeLike
Celebrate
Support
Love
Insightful
Funny
1
- Ming Chang Product Manager @ Meta
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
1. It solves the problem: unless you are a statistician, Excel can satisfy 99% of your needs.2. Do it from a browser: You can use Excel from a browser. Easy to access, easy to collaborate.
LikeLike
Celebrate
Support
Love
Insightful
Funny
1
Load more contributions
2 Cons of Excel
Excel has some limitations and drawbacks that can affect the quality and efficiency of data analysis. These cons include errors and inconsistencies when working with complex formulas, multiple worksheets, and manual data entry. Additionally, Excel can be slow and unstable when working with large and complex data sets, and may crash or freeze. Collaboration and sharing can also be difficult, as Excel files can be large, incompatible, or corrupted, and may require version control and security measures. Furthermore, Excel may be limited in functionality and flexibility, as it may not support some of the advanced data analysis techniques, such as machine learning, data mining, and web scraping. Lastly, Excel can be expensive and outdated, as it requires a license and regular updates, and may not keep up with the latest trends and innovations in data analysis.
Help others by sharing more (125 characters min.)
- Ismael Chang Ghalimi CEO @ STOIC
(edited)
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
In addition, Excel suffers from the following limitations:- Poor data typing system- No native support for modern languages such as Python- No built-in notebook (e.g. Jupyter, Observable)- Limited support for structured data transformations- Slow lookup functions (e.g. VLOOKUP)- Poor user experience when a workbook has many sheets (100 or more)- Limited versioning capabilities- Unfriendly file format (parsing and serializing XLSX is really challenging)
LikeLike
Celebrate
Support
Love
Insightful
Funny
16
- Qiannan Y. Machine Learning Engineer @ LinkedIn
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
I'd say collaboration and sharing is an advantage of Excel rather than disadvantage as most of the time the data to be shared will not be too large to cause issues.
LikeLike
Celebrate
Support
Love
Insightful
Funny
9
- Pankaj Bhagat Marketing Data Analyst | 5+ years in Retail Shop 🏪 | MBA Marketing
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Excel isn't good in Data visualization. Making a good looking functional dashbaord not possible in Excel.BI tools better perform than excel.
LikeLike
Celebrate
Support
Love
Insightful
Funny
1
Load more contributions
3 Alternatives to Excel
Excel is not the only option for data analysis, and there are many alternatives that can offer different features and benefits. For example, Google Sheets is a web-based spreadsheet application that is free, cloud-based, and collaborative, and can integrate with other Google products and services. R is a programming language and environment that is open-source, powerful, and versatile, and can perform a wide range of data analysis tasks. Python is a programming language and framework that is open-source, easy to learn, and flexible, and can work with various libraries and tools for data analysis. Tableau is a software platform that is user-friendly, interactive, and visual, and can create and share stunning dashboards and reports from various data sources and formats. Power BI is a software service that is cloud-based, scalable, and secure, and can connect, analyze, and visualize data from multiple sources and devices.
Help others by sharing more (125 characters min.)
- Sonia Khan BCA Graduate | Administrative Clerk | Clerical Experience in the Judicial Department | Volunteer (UK🇬🇧, Remote) | Passionate Educator
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
I prefer Google Sheets over Excel because it allows real-time collaboration and is accessible from any device. Its integration with other Google tools makes managing projects much easier. #GoogleSheets #Collaboration #Productivity
LikeLike
Celebrate
Support
Love
Insightful
Funny
7
4 How to choose the best tool
When selecting the best tool for data analysis, there is no one-size-fits-all answer as it depends on various factors, such as the type, size, and complexity of the data, the purpose and scope of the analysis, the budget and resources available, and the preference and skill level of the analyst. To choose the best tool, it is important to assess your needs and goals, compare and contrast the pros and cons of different tools, test and experiment with different tools, and seek feedback and advice from other data analysts. Doing so will help you identify the features and functions that are essential and desirable for your data analysis project, evaluate their suitability and compatibility, and learn from their experiences and recommendations.
Help others by sharing more (125 characters min.)
Load more contributions
5 How to improve your data analysis skills
Data analysis is a valuable and in-demand skill that can enhance your career and personal growth. To improve your data analysis skills, you should learn and practice the fundamentals and principles of data analysis, such as data collection, cleaning, exploration, analysis, and presentation. Additionally, you should expand and update your knowledge and skills on different tools and techniques for data analysis, such as Excel, R, Python, Tableau, and Power BI. Taking online courses and certifications on data analysis, and following the latest trends and developments in the field can also be beneficial. Joining online communities and forums on data analysis, networking with other data analysts and experts, and working on real-world data analysis projects can help you apply your skills and knowledge to solve problems and generate insights.
Help others by sharing more (125 characters min.)
Load more contributions
Data Analysis
Data Analysis
+ Follow
Rate this article
We created this article with the help of AI. What do you think of it?
It’s great It’s not so great
Thanks for your feedback
Your feedback is private. Like or react to bring the conversation to your network.
Tell us more
Tell us why you didn’t like this article.
If you think something in this article goes against our Professional Community Policies, please let us know.
We appreciate you letting us know. Though we’re unable to respond directly, your feedback helps us improve this experience for everyone.
If you think this goes against our Professional Community Policies, please let us know.
More articles on Data Analysis
No more previous content
- Here's how you can address constructive criticism from your boss about your data analysis skills.
- Here's how you can advance in your data analysis career by setting clear career goals.
- Here's how you can navigate challenges when transitioning to new data analysis technologies.
- What do you do if you're a data analyst wanting to boost innovation with open-source tools and platforms?
No more next content
Explore Other Skills
- Business Communications
- Business Strategy
- Business Management
- Product Management
- Business Development
- Business Intelligence (BI)
- Project Management
- Consulting
- Business Analysis
- Entrepreneurship
More relevant reading
- Data Analytics What are the limitations of Excel for statistical data analysis?
- Algorithms You’re struggling to analyze your data. What software can help you make sense of it all?
- Business Intelligence What are the advantages of using Excel macros for repetitive data tasks?
- Technological Innovation You need to improve your data analysis skills. What technology can help you?