The use of data mining
Data mining has been getting popularity amongst researchers and leaders nowadays. Numerous studies on data mining have been done to know what data mining really is and how it impacts the business and economy. Research commissioned by Colleen McCue revealed that just like many other methods used in public safety, data mining and predictive analytics can offer several great benefits.
Data mining can be a powerful tool to detect malware, detect intrusion and analyse audit results to detect a malicious pattern, as well as to detect various types of fraud using data mining techniques. It can also be a great source for businesses to identify demand product and/or service in both local and global market. To acknowledge you further on the importance of data mining strategy, let’s dive deeper on what data mining really is…
A brief overview of data mining
The term data mining can be defined as a process of using special software to look at large amounts of computer data in order to find out useful information. For example, you can find out what type of products consumers buy or what kind of articles readers read.
See also: Data Governance for Employees
Frederic De Wispelaere in his study shared that there are two approaches in data mining. First is deduction which begins with an expected pattern/hypothesis that is tested. Second is induction which begins with an observation or data and seeks to find a pattern within process. In addition, applying data mining techniques means you can transform data into actionable information. You can create products which are in high demand, for instance.
In general, there are six classes of processes in data mining: anomaly detection, associate rule learning, clustering, classification, regression, and summarisation. However, you can do pre-processing to analyse the multivariate data sets before data mining. You should also remember that in data mining, you can only uncover pattern which actually presents in data. Therefore, your target data set must be large enough to contain these patterns while remaining concise to be mined. For example, you can use resources from your data mart or data warehouse.
Moreover, data mining also needs result validation to know how well your mining can perform against real data. Craig Guyer explained that validation is important to make your action count. You can validate your mining models by understanding your data quality and characteristics before changing them into actionable production. There are seven tools you can use for mining validation, including partitioning data into testing and training sets, filtering models to train and test different combination, measuring lift and gain, performing cross-validation of data sets, generating classification matrices, creating scatter plots, and creating profit charts.
Data mining and data security
A study by Niranjan Appaswamy and team found that data mining technique is an effective tool to secure your cyber workplace. For example, by using data mining in your cybersecurity, you can process a large database set faster. It helps you create a unique and effective model for each particular use case. Data mining technique also allows you to apply certain data mining techniques to detect zero-day attacks. Zero-day attack, also known as zero-day exploit, is a cyber attack that occurs on the same day a weakness is discovered in your computer software. If you are a victim of a zero-day attack, consequently, the attacker can exploit your data or affect computer programs, additional computers, or a network before a fix becomes available.
Likewise, with various benefits data mining bring, there are certain drawbacks you should be aware of, including its complexity, resource-intensive, and expensive investment. Building an appropriate classifier might also be another challenge you should encounter as a classifier in data mining needs to be constantly updated. Another risk is security issues which include a risk of unauthorised disclosure of sensitive information. Therefore, as a remarkable technique, you should use data mining in a careful way and if possible, you can consult to a data mining expert before allowing your business to reap data mining’s benefits.