Data mining and machine learning – what is it and what is the difference between them?
So it happened. It’s time to admit to yourself in this. Artificial intelligence actively interacts with us, not only in work processes, but also in household affairs.
Despite the distrust caused by the film industry and futurists to AI, it’s time to breathe out and trust it. After all, most routine tasks can easily be deleted from your to-do list now. In particular, you should pay attention to two main technologies – data mining and machine learning.
Data mining and machine learning are mainly focused on helping companies develop decision-making tools without much human involvement. Moreover, the decisions taken may be the basis for action in one direction or another. Do not worry, control is not lost, you yourself can set limits on the freedom of technology. And this “freedom” is conditional. Programs initially study your habits and develop decision-making algorithms that can anticipate your actions, direct you to areas of potential development or useful leads.
Hundreds of problems are solved in a fraction of a second due to the ability to conduct in-depth comprehensive analysis of data that are usually stored randomly and unstructured.
Sounds too good, huh? Let’s understand the principle of operation of each technology separately.
Data mining technology helps in all matters related to data retrieval. Whether it is information about people, concepts, behavior, or about devices that consumers use to interact with the brand. In this case, in a relatively short time, you can scan through terabytes of data and not be out of breath.
Most often, for convenience, companies use data warehousing. Thus, you can at any time conduct the necessary analysis and get working insights for decision-making.
With the help of data mining tools, you can conduct a deep search for the necessary data and find patterns and connections that are unnoticeable at first glance. What the human brain simply cannot physically cope with alone.
Namely, they are important in the analysis of patterns of consumer behavior and to predict a possible feedback.
With machine learning technology, things are a little more complicated. In essence, this is an AI-based system of programs designed to make robots understand the nature of human thought. Yes, we ourselves help robots to enslave our consciousness! But not everything is so fatal. As a result, scientists and engineers hope to get a mechanism for making decisions without human intervention.
At the moment, the forces of AI can predict the reaction of the consumer to your actions. All you need is a database that technology uses as a storehouse of knowledge about past habits of the target audience. Also now is actively developing a new technology – deep learning. Deep learning is trying to repeat the work of the human brain. In the end, scientists want to get to the point where there is no need for a database at all. The whole process of predicting behavior will be automated.
Do not believe it? Let’s return to this question in 5 years.
The main differences between data mining and machine learning:
- Data mining functionality is strictly limited to the collection of information from different resources. The technology itself does not make decisions and is not able to do any actions without human intervention. The main goal is to find useful ways to use the data that have been found.
- Machine learning works with arrays of data that data mining technology has formed. Using pre-modeled action algorithms, AI technology uses data for decision-making and follow-up. Without a constant backup of relevant information, this technology does not exist.
As a result, we get our ecosystem of making informed decisions. Both technologies complement each other, to use them alone is to limit their potential.
Data mining use cases
- Retail uses technology to analyze the target audience. Potential customers can be found focusing on the main characteristics that unite the existing user base. Also, data mining helps to analyze the effectiveness of the service or product of the brand and make a decision about the necessary improvements. Targeting potentially interested consumers is also possible with this technology.
- E-commerce thrives thanks to a deep analysis of the previous history of user activity. Your user recently read about the top 10 places to stay this summer, and you can offer a great offer from your travel Agency? We do not lose time, we establish relations with the client!
Cases of using machine learning
- Business intelligence uses technology to solve different issues. From decision-making regarding different transactions, selection of potentially favorable areas for business development until the formation of conclusions regarding the results of the sales. The technology helps to constantly monitor the “state of health” of your company and offers alternatives in the development and search for new niches.
- Spam mail management is based on AI. Suspicious email attachments or malicious links? Some programs can even remove such emails, preventing the possibility of infection of your PC.
- Online customer service via chat bots is also based on AI. To reduce the waiting time now even the phone calls are answered by bots.
All this is only the tip of the iceberg of the possibilities of the technologies of data mining and machine learning. Dive deeper, study and do not be afraid to entrust your business to the reliable hands of artificial intelligence.