**5. Conclusion**

It's worthy of note to state that time is spent on extracting useful information from data. As a result, in order for companies to develop quickly, it is necessary to make accurate and timely decisions that enable them to take advantage of available opportunities. In today's world of technology trends, data mining is a rapidly growing industry. In order to obtain valuable and reliable information, everyone today needs data to be used in the right way and with the right approach. Data mining can be initiated by gaining access to the appropriate resources. Since data mining begins immediately after data ingestion, finding data preparation tools that support the various data structures required for data mining analytics is important. Organizations may also want to identify data in order to use the aforementioned methods to explore it. Modern data warehousing, as well as various predictive and machine learning/AI techniques, are helpful in this regard.

Choosing which approach to employ, and when, is clearly one of the most difficult aspects of implementing a data mining process. Some of the parameters that are critical in deciding the technique to be used are determined by trial and error. There are clear differences in the types of problems that each data mining technique is best suited for. As a result, there is no simple rule that favors one technique over another.

*The Concept of Data Mining DOI: http://dx.doi.org/10.5772/intechopen.99417*

Decisions are often taken based on the availability of qualified data mining analysts in one or more techniques. The choice of a technique over the other is more dependent on the availability of good resources and analysts.
