Why You Should Consider Software Created Using R Instead of Excel for Your Business Needs

My design using the 2 companies’ publicly available logos

Both R and Excel are excellent choices for a data management strategy and business intelligence. The former is a development language specializing in data science programming while the latter is an application, part of the Microsoft Office suite, used for data management, creating spreadsheets in cells consisting of rows and columns as well as even complex calculations and statistical analysis. It allows for automation as businesses can use it to calculate various metrics as they occur.

These two concepts, one a language and the other an application, often go hand in hand and can both be leveraged within a business for different things. However, consider replacing Excel tasks you rely on for automation and data tracking with software that your programmers can built from the ground up using R and machine learning algorithms.

Why Replacing Excel with R Makes Sense Today

Data science is growing in scope and importance. It is said that data is the new gold for this generation of entrepreneurs. Leveraging machine learning to create propriety solutions in-house can produce much better insight than relying on legacy software solutions hosted by other companies like Microsoft.

R can be used to create smart automation solutions with machine learning algorithms for cutting edge data management, data mining and other tasks. It can do this with propriety or in-house built scripts or code. Thus, instead of using Excel to track metrics and changes within business operations, machine learning solutions created in R can even find faults or holes within business operations that need patching up and solutions to problems can be spotted easier. This is called predictive analytics.

Data Analytics Goes Beyond Data Tracking

Data today is seen as much more than things we can put on charts, such as Excel offers, as much of it is unstructured. It is hard to define or confine by human hands in software. This is the competitive advantage that machine learning or AI offers. Using R to create machine learning solutions can allow your business to find insight from even this unstructured data and use it for business intelligence or predictive analytics.

Data is also much different than a finite natural resource like gold, despite the connotation or comparison, because it has to be used effectively to be useful for a business. Gold has inartistic value – dependent on its supply and the market demand for it at a given time – hence the term the gold standard.

However, data has to be mined, analyzed, and used to find insight. It is also much more infinite in scope as unstructured data can literally be anything a business finds valuable or come from even sources like social media postings occurring at all times.

Excel is more of a tool for gathering and tracking data, while machine learning solutions created in R can actually use it to keep a business ahead of competition and drive future innovation.

Lastly, R is a free and open source solution while Excel requires an Office subscription.