Integrating Artificial Intelligence into Data Warehousing and Data Mining

  • Nelson Sizwe
  • Published 2015


Knowledge engineering is key for enhancing organizational capabilities to gain a competitive edge and adapt and respond to an unpredictable market environment. Such knowledge can be generated from collected data which is often considered complex. Organizations are collecting vast amounts of data to transform them into real-time information in order to attain successful decision-making support systems. It is more than likely that such processes can be challenging; yet such knowledge must be extracted from thoughtfully designed and implemented data warehousing, and mined to obtain the required information. This paper explores appropriate techniques, technologies and trends to facilitate the integration of artificial intelligence into data warehousing and data mining. It provides an insightful overview of data warehousing and data mining, and it highlights the techniques and the limitations of analyzing and interpreting enormous

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Cite this paper

@inproceedings{Sizwe2015IntegratingAI, title={Integrating Artificial Intelligence into Data Warehousing and Data Mining}, author={Nelson Sizwe}, year={2015} }