Abstract
Decision support systems form the core of business IT infrastructures because they let companies translate business information into tangible and lucrative results. Collecting, maintaining, and analyzing large amounts of data, however, involves expensive technical challenges that require organizational commitment. Many commercial tools are available for each of the three major data warehousing tasks: populating the data warehouse from independent operational databases, storing and managing the data, and analyzing the data to make intelligent business decisions. Data cleaning relates to heterogeneous data integration, a problem studied for many years. More work must be done to develop domain-independent tools that solve the data cleaning problems associated with data warehouse development. Most data mining research has focused on developing algorithms for building more accurate models or building models faster. However, data preparation and mining model deployment present several engaging problems that relate specifically to achieving better synergy between database systems and data mining technology.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
