What Is the Difference Between Process Mining and Data Mining?

Both process mining and data mining assist corporate executives in gaining a competitive advantage, but they operate in distinct ways.


Data mining is the process of searching for relationships in large data sets in order to gain new insights. By evaluating static data from databases, we are seeking to transform these hidden correlations into information that we can use for a variety of purposes. Data mining is used in a variety of fields, including scientific research, retail, and media.


Process mining is a relatively young field that arose from the desire to bridge the gap between data mining and business process management. Data mining analyzes big data sets, whereas business process management models, controls, and improves business processes. Process mining bridges the gap between the two by integrating data analysis with machine learning.


What is the Difference Between Data Mining and Process Mining?


Data mining and process mining have certain similarities, but they are not the same. Business intelligence encompasses both data mining and process mining. Both employ algorithms, and in certain cases, machine learning to comprehend massive data. 


While process mining is primarily concerned with creating and fitting information into a process, data mining is more concerned with utilizing the already available data. Data mining is mostly interested with the patterns themselves, whereas process mining is concerned with the why. Process mining is interested in exceptions and the narrative that they provide about the broader problem while data mining discards outliers.


Process Mining and Data Mining Have Similarities


The use of data mining methods and analytical algorithms to sort out business functions with the objective of streamlining and simplifying them to enhance the company's bottom line is known as process mining. The data is the most important aspect of both process mining and data mining.


Both have evolved as components of business intelligence (BI), providing required data for data-backed business decisions. It is natural for data mining and process mining to overlap depending on their origins.

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