Intersection of AI and business intelligence in data-driven decision-making:
In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed r...
Saved in:
| Other Authors: | , , , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania
IGI Global
2024
|
| Series: | Advances in computational intelligence and robotics (ACIR) book series
|
| Subjects: | |
| Online Access: | DE-91 DE-1050 Volltext |
| Summary: | In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive.Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success. |
| Physical Description: | 1 Online-Ressource (xix, 492 Seiten) |
| DOI: | 10.4018/979-8-3693-5288-5 |
Staff View
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| illustrated | Not Illustrated |
| indexdate | 2024-12-17T19:01:36Z |
| institution | BVB |
| language | English |
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| series2 | Advances in computational intelligence and robotics (ACIR) book series |
| spelling | Intersection of AI and business intelligence in data-driven decision-making Arul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors Intersection of artificial intelligence and business intelligence in data-driven decision-making Hershey, Pennsylvania IGI Global 2024 1 Online-Ressource (xix, 492 Seiten) txt rdacontent c rdamedia cr rdacarrier Advances in computational intelligence and robotics (ACIR) book series In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive.Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success. Artificial intelligence Data processing Business intelligence Data processing Decision making Statistical methods Das, Deepthi edt Galety, Mohammad Gouse 1976- edt Iwendi, Celestine edt Natarajan, Arul Kumar edt Shankar, Achyut edt Erscheint auch als Druck-Ausgabe 9798369352885 https://doi.org/10.4018/979-8-3693-5288-5 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Intersection of AI and business intelligence in data-driven decision-making Artificial intelligence Data processing Business intelligence Data processing Decision making Statistical methods |
| title | Intersection of AI and business intelligence in data-driven decision-making |
| title_alt | Intersection of artificial intelligence and business intelligence in data-driven decision-making |
| title_auth | Intersection of AI and business intelligence in data-driven decision-making |
| title_exact_search | Intersection of AI and business intelligence in data-driven decision-making |
| title_full | Intersection of AI and business intelligence in data-driven decision-making Arul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors |
| title_fullStr | Intersection of AI and business intelligence in data-driven decision-making Arul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors |
| title_full_unstemmed | Intersection of AI and business intelligence in data-driven decision-making Arul Kumar Natarajan, Mohammad Gouse Galety, Celestine Iwendi, Deepthi Das, Achyut Shankar, editors |
| title_short | Intersection of AI and business intelligence in data-driven decision-making |
| title_sort | intersection of ai and business intelligence in data driven decision making |
| topic | Artificial intelligence Data processing Business intelligence Data processing Decision making Statistical methods |
| topic_facet | Artificial intelligence Data processing Business intelligence Data processing Decision making Statistical methods |
| url | https://doi.org/10.4018/979-8-3693-5288-5 |
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