Whether an aspiring data analyst or guru in this field, you definitely have sources of information where you frequent to stay up-to-date on best practices and the latest industry happenings. 

However, on this quest, you must have also stumbled upon different outlets that kind of churn out similar content. When you reach this point and feel more lull and in need of something more definite, most people turn to other platforms like Twitter or Wikipedia for a broader perspective, statistics and unique opinions.  

But, if you check up the phrase data analysis on Wikipedia, you will find a detailed explanation with a few technical terms and definitions regarding the multiple facets of the phrase. 

Definition of Data Analysis

While I appreciate the detailed explanations, I was also impressed by the bite-sized explanations of various data analysis gurus we found on the web. Below are a few of the best explanations:

Data analysis is a method in which data is collected and organized so that one can derive helpful information from it.—study.com

Data analytics is the science of analyzing raw data in order to make conclusions about that information. —Investopedia

While these references can give you a better idea of what data analysis is, the key question is, how can data analysis help your business? 

Data analytics is a term that incorporates diverse kinds of data analysis. Any other kind of information may have to go through data analytics techniques to gain more insight aimed at improving things. 

Examples of Data Analysis

As a matter of fact, data analytics can perform more roles than just pointing out existing bottlenecks in production. 

For instance, manufacturing companies often keep records of the downtime, runtime and work queues of various machines and critically analyze the data in order to effectively plan their workloads to enable their machines to run closer to peak capacity.

On the other hand, gaming companies rely on data analytics to create reward schedules for players that make most players active in the game. Content companies utilize these data analytics to ensure users keep watching, clicking or re-arranging content to get a fresh view or click.  


In conclusion, our everyday lives revolve around making decisions whether good or bad. In most cases, people think about what happened previously or what could happen in future and these thoughts inform decisions at hand.

This often involves analyzing past events or future expectations and making decisions based on that. In this case, we collect memories of the past and dreams of our future. That’s a simple illustration of data analysis. And this is exactly the same thing that an analyst does for business reasons, and this is what we call Data Analysis. 

The more general definition of data analysis is the process of checking, cleaning, transforming and modelling available data so as to discover the most useful information to inform conclusions and support your decision-making.   

In short, the purpose of Data Analysis is to extract valuable information from data and making decisions based on the data analysis.