This study explores the data mining techniques adopted by data scientists to solve analytical problems and examines their perceptions and strategies for choosing appropriate methods. In the era of big data, advanced analytics are essential for extracting valuable insights. With a wide range of data mining techniques available, selecting the right one can be challenging, particularly for inexperienced scientists. Using the technology acceptance model (TAM) and an exploratory qualitative approach, this research aims to provide guidance on technique selection. Data were collected through open-ended interviews and analyzed thematically, revealing key strategies and perceptions in data mining adoption.