Data mining

Data mining is the deep process of data collection from a vast database. Data analysis, data statistics, machine learning, and database systems are most essential for data mining. Data mining is the combination of techniques for data collection at the first step. Then, it is to reach the goal of the main process, which is to gather the desired data easily for information gathering. The data mining process involves several steps in data collection. At first, Data Cleaning, like removing the errors in data and cutting out the duplicate data, etc. Then takes data integration like combining the data from multiple sources. Then start the data selection task, like the process of identifying the essential and relevant data set for analysis. Then, data mining involves the data transformation process, like converting the data into a usable format. At last, data mining takes the pattern discovery step by applying algorithms to detect trends. Finally, the Data mining ending task is the process of result evaluation that can assess findings for actionable insights. I can say that, data mining task needs big data, machine learning, deep data analytics, fraud detection, and data-driven decisions. Data mining has become a critical tool in various industries, companies, and many other areas. In conclusion, I will say data mining is a harder process than data scraping. Because a Data scraping task is like a copy job, but data mining involves a complex process.