One of the most important aspects of businesses is databases. You need to rely on software that helps you support your decision-making processes in a matter of a few mouse clicks.

It’s also important to know their limits and investigate how easy it is to manage those programs to solve statistical problems.

Among all the options you have in the market, R and Excel are two of the best and most straightforward data analysis platforms that you can find. They both have advantages and differences that could make you keen on one over the other.

So, how can you tell which one’s better?

This post will cover the main features of Excel and R, their differences, and how you can obtain the best choice for you.

Microsoft Excel is a spreadsheet tool that is part of the Microsoft Office suite. This working program lets you create databases easily and manipulate them in different ways. As such, you can:

• Practice your data entry skills.
• Explore data science to work on complicated data.
• Create pivot tables.
• Quickly create basic graphs.
• Produce charts.
• VBA applies.

Excel gives you the ability to make all this in a few clicks with a substantial benefit and competitive advantage over other spreadsheet programs.

Since its latest update, it has become a user-friendly and powerful tool that complies with the industry standard.

There are plenty of benefits when you use Excel as your data visualization tool.

Easy-to-use Interface

Excel’s interface is extremely easy to handle, especially since its new rework. You can find every tool you need to manipulate very different datasets in the top panel without needing to write time-consuming codes.

Machine Learning

Excel doesn’t have a “machine learning” feature for itself. However, you can use various functions and tools to develop a machine-learning model that can predict changes in your data.

Trendline Function

As a better tool for small datasets than any other, Excel has a Trendline function that allows you to make linear regressions.

Basic and Complex Functions

Excel has different functions for new and expert users. You have everything you need from time series analysis to the new Xmatch function and others to make reproducible research.

Some of the functions you can find are:

• Cost.
• Interest.
• XLookup.
• Count.
• Modulus.

Excel Templates

In Excel, you can use stock templates or download new ones from a third-party website. With these outlines, you can change your data frame, create graphs and charts with ease.

Rows and columns and be edited too to modify the entire data process.

Almost Unlimited Rows

Excel can handle a big data set thanks to a high number of rows and columns. However, most people have a sheet underperforming after adding too many variables, values, graphics, and calculations.

Consistent Updates

Microsoft Excel – as well as  all Office apps – has constant updates to ensure its functionality and security.

It also counts that version control is needed to work with the Microsoft 365 integration.

Collaboration Tools

The collaboration tools were first seen on Google Sheets. These features allow you to work together with other people in real-time, communicate via internal chat, send comments, suggestions and work on a new data set from scratch.

Of course, you need a Microsoft 365 account to have the integration completed.

R is an open-source code program that you can use to create a statistical environment. As such, you can use the R source code to manipulate data, create a pivot table and handle big data without issues.

The R programming language has different statistical and graphical features that lead users to choose R over Excel. These include but are not limited to:

• Nonlinear modeling.
• Text Mining.
• Capabilities to handle large data sets.
• Time-series analysis.
• Clustering.
• Graphs.
• Scripts.
• Mapping.
• Reproducibility.
• Resources to automate arithmetic functions.
• Trend analysis.

As an open-source and free product, you can modify it to your business needs.

R users claim this is the right tool for your company when you want to manage larger data sets. Why is that?

Users’ conclusion explains that R has better statistics compatibility when you compare it to Excel. Memory is not an issue either and the expected results are capable of saving people’s budget – but that also applies to Excel.

Below we mention the most important features of R.

Solid Design

In comparison to other programming languages, R is a good tool with an intuitive user interface. Since its beginnings, it has passed over a lot of changes. Now, it has become software with the same design and aesthetics as Excel.

You have direct access to the toolbar, and you can even preview charts or graphics before you create them. Thanks to that, you have complete control over the type of data you’re manipulating.

Special For Complex Work

Compared to Excel, R has packages that include functions and other statistical functions to do specialist work.

Some of the formulas you can find are:

• Regression analysis.
• Search.
• Difference.
• Trends analyses.

Community-Driven Software

As free software, the community has absolute control over the future of the project. That said, you can find knowledge in a group of people when you need help. If you don’t know how to start, they can lead the way for you.

They got your back if it doesn’t make sense to you how to reproduce a chart or anything else. Once you’ll get familiar with them, you can also contribute with what you’ve learned.

As you can see, they have similarities. But how can they differentiate from one another?

Below, we have developed a table comparison so you can know which is the best data analysis tool for you.

After this comparison, which software is the best for you?

Based on our opinion and experience, Microsoft Excel is a solid choice when you want to create a graph or develop a short, medium, and even large dataset. It also works when you want to set up formulas that lead you from point A to point B.

You don’t need any script or any other add-on to work with Excel. It has everything you need to start building up your data analysis environment.

Of course, if you need software that stores big data and extremely large databases, R will work better for you.

The main issue to get Excel, is that you need to pay for a license that costs over $150. That’s a lot of money for an entrepreneur, small businesses, or even corporations that don’t want to pay that amount for a software.

So, what can you do?

You can use a third-party website like RoyalCDKeys. Here you can find original and trustable licenses for pennies. As such, you’ll find here Microsoft Office 2021 for over $12.

This is a lifetime license, which means that you only have to pay it once.

After getting the CD key, you can activate your software during or after its installation.

There are lots of data analysis tools available in the market – such as Python or R. But in comparison to Excel, they can seem intimidating and with an initial learning curve that could be more or less difficult for you to pass.

In this comparison, we explored R – an open-source programming language and a data analysis tool – and Microsoft Excel and their ability to read, edit and manipulate different datasets.

Among those two, Excel is the clear winner. Not only because it’s easier to use, but because you get other attributes that you wouldn’t enjoy with R. 

For example:

• Collaboration features to work with other people.
• Continuous updates.
• Intuitive interface.
• Programs available from the Microsoft Office suite.