In our last post, we talked about the vital role of machine learning to facilitate business processes. In this post, we will narrow down the use of data-mining in different service providing industries.
As cloud-computing and data collection are becoming increasingly integrated with our daily activities, large amounts of unstructured data are also being collected. It combines techniques from disciplines of AI with machine learning and statistics to leverage data-processing. Nevertheless, the data-mining process cannot be limited to collecting or mining data as the term suggests. Data-mining uses tools to help determine an organization’s current progressive status, level of market competition and market trend, and the overall decision making process.
Let’s look at how different industries are using data-mining:-
Finance and Accounting
In finance and accounting, data-mining has roles of utmost importance. Data-mining enables such organizations to predict and potentially avoid financial distress or even bankruptcy, get insight on the preliminary financial status, detect management fraud and flaws, estimate credit risks, and predict overall corporate performance. Data-mining tools put forth a better picture of market-risks and develop strategies to maximize return on investment.
The boom in the use of the World Wide Web has brought about simultaneous influence in web-mining and making data-mining more visible in e-commerce. Data-mining is applied to study consumer behavior and forecast sales. It also provides intelligent insights for cross-selling and up-selling products. With data-mining software, organizations can discover trade tendencies and select the most feasible option from an array of alternatives.
The contemporary healthcare industry covers a much broader spectrum than ever before, creating vast records of patients, cases, resources, disease diagnostics, medical devices, etc. Data-mining comes in handy when data in bulk is required to be processed and analyzed for extraction of precise information. This helps in minimizing cost and aids in decision making.
Data-mining can also manage patient relationships, prevent insurance abuse, and reduce healthcare costs. It is a powerful tool for physicians to evaluate treatments and to conduct medical research.
Sales and customer history related to data collection are done in large quantity. Moreover, introduction of web and e-commerce in the retail sector has given easier access to buyers and increased business popularity globally. Applying the insights can help retail industries manage inventories, balance stocks and forecast sales. It can also make marketing campaigns more effective and improve customer retention.
The concept of educational data-mining is still in its developmental stage. In educational sectors, data is collected from students’ involvement in interactive learning environments, computer-supported collective learning, or administrative data. The data collected comes in layers of relevant ranking, which requires further processing to be identified by properties in the accumulated data. The importance of data-mining in education and academics can be highlighted to measure students’ performance and interests.
Data-mining in manufacturing has a wide area of influence. Areas in which data-mining tools help function effectively are: production processes, operations, fault detection and maintenance, decision support and quality control. Manufacturing patterns of complicated production procedures are further discovered, which ultimately leads to improving product quality and understanding the contemporary market demands. The use of data-mining in manufacturing can also help to determine cost and pricing.
Telecommunication companies generate data in tremendous amounts. Call details, network data, and consumers’ telecommunication data are all gathered by data-mining tools. Data-mining in telecommunications can be used to detect and prevent fraud. Identification of fraud by comparing consumers’ calling behavior with recent activity helps detect and then prevent scams. Telecommunication companies also store call detail records, which shows calling patterns of consumers. This helps companies keep marketing/customer profiles.