Without knowledge and information about whatever is going on around the world, a person can never become a part of the human race, participate, and succeed at it. The point is to always be aware and alert of your surroundings. The motivation for this activity is to get more involved in life and to do it in the right way. By “right way” we mean being intellectually, physically, socially, spiritually, and culturally aware of how things are taking shape around us.
Knowledge is power and you can’t deny that. If you have good knowledge about things, you can interact, convince — achieve whatever it is that you want. The only key to that is developing understanding. This applies everywhere; whether you are dealing with any relationship, business deal, or solving a mathematical sum – a sound understanding of your subject matter would always go a long way. Having said that, we do not overlook the significance of talent and skill that further adds to make the task possible – whatever it is that you are on. In the modern-day world, you have the option to learn anything by staying online; all you need is an internet connection like Spectrum Internet® to unfold the world of knowledge that is available online.
Moreover, in this article, we will discuss how “understanding” a specific area of your interest would help you be more successful at whatever it is that you want to do. Speaking of which, we are to discuss in this article the importance of data mining and machine learning to govern and lead a business. But before we talk about their role in the business department, let’s have a little overview of the basic differences between both terms.
Machine Learning
Machine learning is a sub-branch of artificial intelligence that helps robots learn the behavior of humans. The reason for discovering this is to promote the idea of self-governance for the machines that would be able to make decisions on behalf of humans without their supervision. But that’s not entirely what machine learning is about. It is also about collecting data on human behaviors, choices, desires, nature – everything related to them, through the internet search engines they use. These search engines could be Google, Wikipedia, social media forums, or any website they log in to through the internet. Internet indeed has remarkably revolutionized the course of time. It helps to lead people to their interests by analyzing their interests.
Data Mining
It is the process of collecting data of every choice, selection, the interest of humans that they consciously or unconsciously make while using the internet on Google, Facebook, Twitter – any website they click. Every click made by a user of the internet is recorded, analyzed, and processed to make an assessment of what they want, and in response what should be offered to them. The human traffic, in a strategic way, is then led by machines (computers) to the hub of their interests.
The basic difference between the two is that data mining is the process of collecting and storing all the data while machine learning is all about training a device to make use of that data to direct the traffic towards their places of interest.
It is an excellent tool in the field of marketing. Marketing departments take immense advantage of this strategy by creating useful ideas for the pitches, and campaigns to the corporate world so as to fascinate their target audience; this means that businesses develop and quickly grow when they have smart marketing departments.
As mentioned before, learning and understanding the surroundings and the developing age is necessary to be able to formulate ideas that could benefit one’s own interests and movements. These new ideas can give a turn to the trends. These turns may not be too sharp, for the fear of complete rejection by the public; they have to be smooth and reflective of the roots they emerge from.
Where has Data mining been used in businesses?
The answer to where it has been used so far in developing businesses is predictable- Retail. Most retailers use the data collected through data mining in order to make their decisions. It greatly helps them in learning what type of customer would find their goods attractive. So basically, data mining is helping retailers to learn about their audience, their target audience, and the general public that could be interested in their products.
Another area that has been benefitting immensely from this type of learning is e-commerce.
All the data received from the public about their interests and likes has great significance in bringing the businesses closer to their target customers. E-commerce companies get into data mining to get a deeper insight into their audience. If you have ever seen advertisements on your screen that show the exact thing that you were searching for a day before, then there are good chances that an e-commerce company has strategically gotten a hold of your interest through your clicks and likes and presented to you the objects of your interest.
It is also an extremely smart way of selling well to the people who are randomly scrolling through the newsfeed of their social media account. The shopaholics suffer through the intense desire of purchasing the product of their interest once it reaches them by “randomly” showing up on their screens. With all the lectures on data mining and machine learning, you can safely say that it, in fact, is not random or coincidental.
Data mining also helps police departments and other authorities to know where they have to focus their resources. These departments use data patterns and designs to find surges in a reported crime at a specific place, at a specific time. This practice helps them locate the reason for the occurrence of the unfortunate incident. The tracking efforts made by the local, state, or federal agencies also become easier with data mining.
Wrapping Up
In conclusion, machine learning and data mining are two very important fields of study. Machine learning is a method of teaching computers to learn from data, without being explicitly programmed. Data mining is the process of extracting valuable information from large data sets. Both fields are important for businesses and organizations to understand and use in order to make better decisions.
