Knowledge Base Article

Data Mining 101

Data mining is the process of finding patterns in data. The beauty of data mining is that it helps to answer questions we didn’t know to ask by proactively identifying non-intuitive data patterns through algorithms (e.g., consumers who buy peanut butter are more likely to buy paper towels). However, the interpretation of these insights and their application to business decisions still require human involvement.

Data mining is most commonly defined as the process of using computers and automation to search large sets of data for patterns and trends, turning those findings into business insights and predictions. Data mining goes beyond the search process, as it uses data to evaluate future probabilities and develop actionable analyses. Machine learning, meanwhile, is the process of teaching a computer to learn as humans do. With machine learning, computers learn how to determine probabilities and make predictions based on their data analysis. And, while machine learning sometimes uses data mining as part of its process, it ultimately doesn’t require frequent human involvement on an ongoing basis (e.g., a self-driving car relies on data mining to determine where to stop, accelerate, and turn).

 

Updated 8 months ago
Version 18.0
  • This is a great topic of conversation and a direction we're thinking of taking with our Data Nexis and Data Master tools.