Today’s risk management and strategic decision making are fueled by data collected from a variety of sources. Because most of this data is unstructured, data mining software can transform it into understandable and actionable knowledge.
What is data mining and how does it work?
Data mining is the process that applies a variety of methods to identify previously unknown correlations and patterns in large volumes of data. These methods include semantics, statistics, artificial intelligence and machine learning. The goal of data mining is to transform information into something structured and understandable so that it may be used in a number of downstream information- and knowledge-based processes.
In this post, we look at some of today’s trends in data mining software usage.
Data mining software for predictive analytics and insight
Data-driven decision making depends on data mining software to discover the patterns and anomalies that can be used to forecast future trends. Data mining software excels at extracting and consolidating data from the variety of internal and external sources, including multiple enterprise systems, that businesses depend on. Using the insight gained from unstructured data, companies can uncover the relationships between internal and external factors that can potentially impact any aspect of the business, especially related to customers. Market analysis for developing new product lines, competitive analysis are just a couple examples of how businesses are using data mining for predictive analytics.
Data mining software for medical data analysis
More recently, data mining software has been applied in the life sciences and medical sector, particularly in areas such as bioinformatics and general medicine. In the medical field, data mining software is used to extract knowledge from vast databases and identify weaknesses and best practices in order to reduce the costs and improve patient care. Researchers are using data mining software to discover trends in their field and to avoid replicating existing studies.
Health systems can benefit from using data mining systems to identify at-risk patients and ensure that they receive the appropriate care, or deliver monthly reports to demonstrate compliance with internal or external standards of care. Another great example of using data mining software is predicting health risks within specific populations.
Data mining software to expand and protect your business
The way in which customers engage with companies, services or products has changed. Today, companies are present on the most common platforms such as Facebook Messenger, WhatsApp and Twitter because that’s where customers are. One result of this is the proliferation of valuable unstructured data on these channels. Data mining software can help companies collect this information and use it for a variety of purposes, from targeted marketing, to behavior and market analysis. Data mining software is being used in both insurance and finance to predict and identify fraudulent practices, from insurance claim scams to insider trading. It may also be used to forecast which customers will buy new policies through predictive pattern modeling.
Among some of the more unique applications of data mining, computer scientists at the University of Oklahoma are studying tornadoes using a combination of data mining and visualization techniques to explore the factors that separate tornado formation from tornado failure.
With unstructured information making up more than 90% of the data in our digital universe, data mining software usage is increasing among organizations in every sector that are discovering the predictive and analytic power of this technology.
