Data mining is widely used in different industries today because of its strong focus on consumers particularly in retail, financial, as well as marketing organizations, and communication because of its ability to drill down into different transactional data which determines the preferences and pricing for customers as well as positioning products, give customer satisfaction and the impact on sales and corporate profits.
Because of data mining, the retailer can now accurately use it for point-of-sale that records of customer purchases that is aimed to develop products and promotions which appeals to a specific customer segment.
In this article from Elasticsearch Query tutorial, let us talk about the importance of data mining in consumer, retail, and financial to give you a wider view about this magnificent process. Before we proceed with the rest of the article, it would be appropriate to know what is data mining in the first place?
Data mining is the process that is used to analyze the hidden patterns of data according to different perspectives to categorize it into a very useful information and then collected and assembled to common areas, such as data warehouses, for analysis, algorithms, and to facilitate business decision making and other required information to cut costs and increase revenue for a particular business. In short, data mining is also known for experts as data recovery.
Below we listed down some of data mining’s uses in different industries to make you feel more appreciative of this process which is always overlooked by many.
In the healthcare industry, data mining holds a big role and a big potential in improving the health systems by using the data analytics in identifying the best practices which is aimed to improve care and reduce the costs as researchers uses this process as an approach like multi-dimensional databases, soft computing, data visualization, statistics, and machine learning. Data mining can also be utilized to predict the number or volume of patients in a medical category to ensure that the patients will receive appropriate medical care at the perfect timing. Data mining can also improve healthcare insurers to find out any fraudulent abuse from the insurance companies that they deal on.
MARKET BASKET ANALYSIS
In case you do not know, market basket analysis is a modelling technique or method that is based upon a theory that if you purchase a certain group of items, you are more likely to purchase it in another group of items, and this type of technique can allow the retailer to fully understand the behavior of the buyer whenever they purchase a product. This information that the data mining recovers will help the retailer to determine the needs of the buyers and change their approach in lay outing their stores according to the demand. This can be done by using differential analysis comparison between the results of different competitors, between customers based on different demographic groups like the Weka data mining tutorial.
Data mining can now be used in the education sector to further develop methods in discovering knowledge from data originating from educational environments. Educational Data Mining or EDM is identified to predict the future learning behavior of each student by studying the effects of how educational support and advancing scientific knowledge affects a student’s comprehension. Data mining can also be used in an educational institution to come up with a more accurate decision and also to predict the examinations of a student.
Manufacturing enterprise’s best asset is knowledge where data mining perfectly fits the demands of it by using the needed tools that can be very useful in discovering the patterns of a complex manufacturing process. Data mining just like what the Ansible AWS tutorial uses in manufacturing enterprise, it utilizes through a system-level designing for the extraction of product architecture, product portfolio, and customer needs data and determines its relation to each other. It can also be utilized in predicting the development of a product in a time period, as well as its cost, and its dependence on other tasks at hand.
Annually, there are billions of dollars lost in fraud and most security systems use traditional methods which are becoming obsolete and time consuming that is why data mining comes in as a more effective tool in creating meaningful patterns and transforms data into information. Data mining is considered a perfect fraud detection system that mainly aims to protect information of all the users. Data mining collects the sample records and identifies it if it is fraudulent or not.