Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/72031

TítuloIntegration challenges for analytics, business intelligence, and data mining
Autor(es)Santos, Manuel
Azevedo, Ana
Palavras-chaveBusiness Intelligence
Data Science
DataDez-2020
EditoraIGI Global
CitaçãoAzevedo, A., & Santos, M. F. (Eds.). (2021). Integration Challenges for Analytics, Business Intelligence, and Data Mining. IGI Global. http://doi:10.4018/978-1-7998-5781-5
Resumo(s)As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students.
TipoLivro
URIhttps://hdl.handle.net/1822/72031
ISBN1799857816
e-ISBN9781799857839
DOI10.4018/978-1-7998-5781-5
Versão da editorahttps://www.igi-global.com/book/integration-challenges-analytics-business-intelligence/253124
AcessoAcesso restrito autor
Aparece nas coleções:CAlg - Livros e capítulos de livros/Books and book chapters

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