Software, Technology, And Data Analysis

When it comes to technology, software, and analyzing data, we tend to think of the biggest companies in the world. Google, Apple, Cisco, but does Nike Running app use data? Of course. There is a pattern and system of doing business that allows large companies to scale so much that most of the population is enticed to buy their products. The pattern is that of looking at data and analytics by testing products and ideas. In this article, we will discuss how businesses and non-profits can use data analysis to improve their systems, with an emphasis on data analysis for running apps.

Software, Technology, And Data Analysis

Data analysis is the process of gathering, organizing, and inspecting data to find trends, irregularities, and other specifics. Data analysis, for example, can tell you on what days a website receives most of their visitors. It can also show you the times in which users are more active. I myself use this through the Instagram and Facebook analytics platform so that I know the days and times when my followers will most likely see my posts.

Data analysis and app data have been a huge factor in helping people stay healthy. There are apps that will track your calories, the number of steps you take, the miles you run, and how it is affecting your health. By looking at large amounts of user data, we can make a conclusion on the averages of these users.

For example, taking data from six different running apps, we can deduce that the most popular time for people to go on a run is after they get off work at around 5:00pm. Looking at this data, we can also make conclusions on what type of person uses a certain app.

Going back to the statement we made in the introduction, data can and has helped major businesses improve their systems, their marketing, their sales, to create new and better versions. Companies often do this by testing products to a small test group. When the results come back, they do the same data analysis that the running apps use. They are then able to deduce what changes must be made, what is not working, and what to continue to use.


In conclusion, in this article we explained what data analysis is, and how it is used for different areas. It is commonly used in social media, health and exercise apps, and has been used to grow and create better businesses that serve customer needs. Though it sounds simple, it is harder than it seems to get enough data to analyze, but luckily, with our current technology, we can easily plug in formulas to make conclusions. If you like running through data, we hope this article gave you a good warm up.