Mrinal Singh Walia — June 11, 2021
Beginner Computer Vision Data Mining

This article was published as a part of the Data Science Blogathon

Data mining is a technique of extracting and finding patterns in massive data sets by linking practices at the intersection of machine learning, statistics, and database management systems. Today’s article is about what data mining can do for your company, and after that, we will look into some of the practical use cases of data mining in your company.

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Photo by Carlos Muza from Unsplash 

Why Does Your Company Needs Data Mining

Many consulting firms in the industry can help your company better utilize their data, from capturing it to analyzing it consistently with industry standards and beyond what others currently do with their data.

There is a wealth of knowledge and expertise to be gained and gleaned from the data that your company could capture, and it is essential to learn how to utilize that data and make more informed business decisions.

What Should Companies Do?

Many consulting firms offer to consult services to help you understand what your data is saying to you and your company. It also helps with the planning and full-scale implementation of any new data program.

As data consultants, companies should focus on the complex and exciting problems that your data will lay bare for your company. There is often no other way to find out what the issues are or what the real cause of the problem is until you capture the data, drill down into it and organize it so that you can see the patterns and get a better understanding of where the problem is coming from.

This is likewise valid for organizations that do not spawn any issues but are not moving forward with new initiatives or growing at the required or desired rate. The data consultants in a company do this data mining, and then that data is analyzed to find those previously unknown patterns to your company.

Many new ideas are brought to the previously unseen or unknown surface with this form of data analysis. This is the power of data, massive data.

How Data Mining Benefits Your Company If Done In The Right Way

 

How Data Mining Benefits Your Company If Done In The Right Way
Photo by Franki Chamaki from Unsplash

If you have data coming in that is not being captured and stored for that analysis, it needs to be charged. Data mining experts can work for you to have a system to capture your data and then ensure that you can review and analyze the data to make sense around the company and to the top leadership.

Information is only practical if learned, and experts cannot make decisions until it is clear and valuable. This is where the consultants and their data mining come in, and this is why you would hire data mining experts to perform data mining for you.

Once you ought the method set up, you can enter the info you want to see, and the system will provide it for you. The data will be there, fully captured and organized, tagged, and fully ready for analysis. It just takes a trained consultant to show you what the data is saying and teach you how best to use those dates for your company’s future decisions.

Practical Uses of Data Mining in Businesses

Data mining is not something new. Over time people have been gathering information to use for whatever purposes it suits them. Both sides will always try to find out just how large the other force is in times of war.

This way, they will be able to make the necessary adjustments or strategies. Unprocessed data also referred to as raw data, are, in fact, meaningless. It is only when the data is processed that it starts to have meaning. Data mining is defined as a way of converting raw data to something useful.

In the past, data analysis was limited to a group of people who had the necessary skills needed to interpret it. Today, however, there are now many different companies that offer analytics consulting or data analysis consulting. It is essential to know that there is a difference between data analysis and data analytics.

Know The Difference Between Data Analysis and Data Analytics

Data analysis is when you gather data from different sources then make it into something useful. Data analytics, meanwhile, is a platform wherein you use other models on the data to get additional insights.

Still, confused about the difference between the two? Let’s have a simple example. Suppose a convenience store decides to look at its sales on Fridays. Through data mining, it finds out that beer sales increase during Fridays. Data analysis consulting would likely tell you what percentage of the Friday sales is for beer and what type of beer customers prefer. Undergoing analytics consulting, meanwhile, would include information like what time during Fridays do customers buy beer.

By using these different sets of data, the owner of the convenience store can do several things. First, the owner can ensure that there is an ample supply of beer during Friday nights. Alternatively, the owner can also decide to offer discounts on other days, knowing full well that sales are relatively low during other days. Regardless of what decision the owner makes, the end goal is always using the information to increase profits.

So what did the owner do?

First, the owner did some data mining by getting figures for the number of beers sold on Fridays and the types of beer sold. Conducting data analysis consulting these results will give the owner a picture of how his store is faring on Friday nights.

Yet, the owner does not stop there and does analytics consulting new additional factors like time of sale. This, in turn, will give the owner a clearer picture, and the owner will be able to act accordingly, ensuring an increase in sales.

Last Point To Notice

Remember that everything, the raw data mainly, has always been available to the owner. The owner simply needed to find a way to make sense of everything before taking any new action. This is the primary purpose why corporations should adopt this and grasp this in mind. Data mining indeed can help enterprises to but only when companies know how to use whatever was gathered and apply the knowledge gained accordingly; otherwise, it will just be meaningless numbers.

If you enjoy reading this article, I am sure that we share similar interests and are/will be in similar industries. So let’s connect via LinkedIn and Github. Please do not hesitate to send a contact request!​_

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