Data mining is a process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistic, and database systems. It is an interdisciplinary subfield of computer science and statistic with an overall goal to extract information from a data se. And transform the information into a comprehensible structure for further use.
Data mining is the analysis step of the “knowledge discovery in databases” process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing. And inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.
The actual data mining task is the semi-automatic or automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection), and dependencies
How is data mining done?
It involves exploring and analyzing large blocks of information to glean meaningful patterns and trends. Then, application software sorts the data based on the user’s results, and finally. And the end-user presents the data in an easy-to-share format, such as a graph or table.
Where is it applicable?
Banks use data mining to better understand market risks. It is commonly applied to credit ratings and to intelligent anti-fraud systems to analyze transactions, card transactions, purchasing patterns and customer financial data.
Disadvantages:
- Cost-It involves lots of technology in use for the data collection process.
- Security- Identity theft is a big issue when using this.
- Privacy-When using this there are many privacy concerns raised.
- Accuracy.
- Technical Skills.
- Information Misuse.
- Additional Information.
Why is this dangerous?
While this on its own doesn’t pose any ethical concerns, leaked data and unprotected data can cause data privacy concerns. Through the years, there have countless campaigns on stolen data that have caused an uproar in various parts of the world.
