Technological innovations have much changed the ways of retrieving information, that has been accumulated over long years and, is consistently expanding. Extracting critical information out of this voluminous data, however, could be challenging, and thus businesses require sophisticated tools and techniques in place.
To help them, gradually the concept of ‘data mining’ came into existence as a subset of knowledge management and discovery. Particularly, this is a technique which performs data processing with the help of statistical algorithms to retrieve and analyze hidden information from the large untouched databases, and reveal significant correlations and patterns hidden within.
In essence, data mining has transformed the information world to a great extent. By analyzing data from the different perspective, it has offered numerous inevitable advantages to businesses, information seekers, database developers, researchers, etc. and helped them to make informed decisions. Simply, digging deep into the data and categorizing it enables mining of data specialists to determine the hidden predictive information that businesses require to determine the market, competition, upcoming trends and, right business strategy.
Considering the raw data, it can exist in any form- analog and digital based on its source, and to analyze it, one would need to implement data mining techniques to receive valuable output. The techniques, on the other hand, can vary from basic to complex depending on the purpose that needs to be served. Companies outsource this services because of the capability of analyzing data from the different perspective in order to find out some interesting patterns as well as to find some new business opportunities. Let’s discuss some techniques in detail:
· Cluster Analysis is a technique that determines patterns within large data sets. It’s more about arranging a set of data into groups where each object is similar to other objects in the same group. It is extremely useful for recognizing patterns and doing market research.
· Anomaly detection focuses on finding non-similar objects/patterns in datasets. This technique can be applied to detect anomalies in weather patterns, medical problems, text errors etc.
· Regression analyzes several variables and determines the relationship between them. By analyzing large datasets, it predicts future outcomes and thus, enhances user engagement and customer retention.
· Association technique identifies patterns by analyzing the relationship between two or more data/objects which are correlated with another object or in simple words, are more likely to occur together.
Benefits of data mining:
Data mining plays a signification role in accomplishing business’s goals and objectives. Enlisted are some advantages of the this services across various industries:
· Marketing industry: Marketers can take the huge advantage ofdata mining services in order to make their marketing campaigns a huge success. By having insights into customer’s behaviors and their interests and, latest market trends, they can shortlist products that customers want to buy more. This, in turn, can help retailers or store managers to arrange their shelves, stock products or allure more customers with amazing offers/discounts. Additionally, data mining help to identify targeted customers, best customers, and profitable marketing campaigns strategies as well.
· Banking/Finance Industry: Applying data mining techniques in financial institutions has got its own advantages. It provides critical information about customers and their interests in credit cards and loans services. It can build’s customer’s profile and creates risk models for credit cards, loans, and mortgages. Also, it assists banks in identifying fraudulent credit card transactions.
· Retail industry: Like marketing, data mining help retail companies through Market Basket Analysis (MBA) or product affinity analysis. Basically, MBA is all about identifying the items which customers like to buy together frequently in order to facilitate appropriate production arrangement. This way companies can have a clue about best-sold products and they can promote them or can offer certain discounts to gain more customers.
· Corporate Businesses: In IT businesses data mining assists in monitoring a person’s behavior or day-to-day activity. It indicates that it helps in generating business intelligence that ultimately helps to deliver high-quality products/services.
· Medical and healthcare institutions: In medical institutions, data mining brings lots of benefits by determining the relationship between certain diseases, their treatments, medicines etc. Pharmaceutical manufacturing companies can boost their sales by determining latest diseases or the diseases which are going to impact in coming months.