Integration Of Data Mining In Business Intelligence Systems
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Integration Of Data Mining In Business Intelligence Systems
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Author : Azevedo, Ana
language : en
Publisher: IGI Global
Release Date : 2014-09-30
Integration Of Data Mining In Business Intelligence Systems written by Azevedo, Ana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-30 with Computers categories.
Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.
Integration Challenges For Analytics Business Intelligence And Data Mining
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Author : Azevedo, Ana
language : en
Publisher: IGI Global
Release Date : 2020-12-11
Integration Challenges For Analytics Business Intelligence And Data Mining written by Azevedo, Ana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-11 with Computers categories.
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.
Integration Of Data Mining In Business Intelligence Systems
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Author : Ana Azevedo
language : en
Publisher:
Release Date : 2015
Integration Of Data Mining In Business Intelligence Systems written by Ana Azevedo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Business intelligence categories.
"This book investigates the incorporation of data mining into business technologies used in the decision making process, emphasizing cutting-edge research and relevant concepts in data discovery and analysis"--
Microsoft Data Mining
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Author : Barry de Ville
language : en
Publisher: Digital Press
Release Date : 2001-05
Microsoft Data Mining written by Barry de Ville and has been published by Digital Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-05 with Computers categories.
This guide teaches data mining from the perspective of IT professionals using Microsoft data management and e-commerce technologies. The book explains major new data mining capabilities in the forthcoming SQL Server 2000, Microsoft Commerce Server, and other products, and details the new Microsoft standard, "OLE DB for Data Mining".
Business Intelligence Guidebook
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Author : Rick Sherman
language : en
Publisher: Newnes
Release Date : 2014-11-04
Business Intelligence Guidebook written by Rick Sherman and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-04 with Computers categories.
Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors’ tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled – projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers. After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget – turning the deluge of data into actionable information that fuels business knowledge. Finally, you’ll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success. Provides practical guidelines for building successful BI, DW and data integration solutions. Explains underlying BI, DW and data integration design, architecture and processes in clear, accessible language. Includes the complete project development lifecycle that can be applied at large enterprises as well as at small to medium-sized businesses Describes best practices and pragmatic approaches so readers can put them into action. Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources.
Real World Data Mining
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Author : Dursun Delen
language : en
Publisher: FT Press
Release Date : 2014-12-16
Real World Data Mining written by Dursun Delen and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-16 with Business & Economics categories.
Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: processes, methods, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials. Real-World Data Mining will be valuable to professionals on analytics teams; professionals seeking certification in the field; and undergraduate or graduate students in any analytics program: concentrations, certificate-based, or degree-based.
Improving Knowledge Discovery Through The Integration Of Data Mining Techniques
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Author : Usman, Muhammad
language : en
Publisher: IGI Global
Release Date : 2015-08-03
Improving Knowledge Discovery Through The Integration Of Data Mining Techniques written by Usman, Muhammad and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-03 with Computers categories.
Data warehousing is an important topic that is of interest to both the industry and the knowledge engineering research communities. Both data mining and data warehousing technologies have similar objectives and can potentially benefit from each others methods to facilitate knowledge discovery. Improving Knowledge Discovery through the Integration of Data Mining Techniques provides insight concerning the integration of data mining and data warehousing for enhancing the knowledge discovery process. Decision makers, academicians, researchers, advanced-level students, technology developers, and business intelligence professionals will find this book useful in furthering their research exposure to relevant topics in knowledge discovery.
Progressive Methods In Data Warehousing And Business Intelligence Concepts And Competitive Analytics
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Author : Taniar, David
language : en
Publisher: IGI Global
Release Date : 2009-02-28
Progressive Methods In Data Warehousing And Business Intelligence Concepts And Competitive Analytics written by Taniar, David and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-28 with Computers categories.
Provides developments and research, as well as current innovative activities in data warehousing and mining, focusing on the intersection of data warehousing and business intelligence.
Fundamentals Of Business Intelligence
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Author : Wilfried Grossmann
language : en
Publisher: Springer
Release Date : 2015-06-02
Fundamentals Of Business Intelligence written by Wilfried Grossmann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-02 with Computers categories.
This book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making. To that end, the authors develop step-by-step models and analytical tools for obtaining high-quality data structured in such a way that complex analytical tools can be applied. The main emphasis is on process mining and data mining techniques and the combination of these methods for process-oriented data. After a general introduction to the business intelligence (BI) process and its constituent tasks in chapter 1, chapter 2 discusses different approaches to modeling in BI applications. Chapter 3 is an overview and provides details of data provisioning, including a section on big data. Chapter 4 tackles data description, visualization, and reporting. Chapter 5 introduces data mining techniques for cross-sectional data. Different techniques for the analysis of temporal data are then detailed in Chapter 6. Subsequently, chapter 7 explains techniques for the analysis of process data, followed by the introduction of analysis techniques for multiple BI perspectives in chapter 8. The book closes with a summary and discussion in chapter 9. Throughout the book, (mostly open source) tools are recommended, described and applied; a more detailed survey on tools can be found in the appendix, and a detailed code for the solutions together with instructions on how to install the software used can be found on the accompanying website. Also, all concepts presented are illustrated and selected examples and exercises are provided. The book is suitable for graduate students in computer science, and the dedicated website with examples and solutions makes the book ideal as a textbook for a first course in business intelligence in computer science or business information systems. Additionally, practitioners and industrial developers who are interested in the concepts behind business intelligence will benefit from the clear explanations and many examples.
Business Intelligence Guidebook
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Author : Rick Sherman
language : en
Publisher:
Release Date : 2014
Business Intelligence Guidebook written by Rick Sherman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Data mining categories.
Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors' tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled - projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers. After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget - turning the deluge of data into actionable information that fuels business knowledge. Finally, you'll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success. Provides practical guidelines for building successful BI, DW and data integration solutions. Explains underlying BI, DW and data integration design, architecture and processes in clear, accessible language. Includes the complete project development lifecycle that can be applied at large enterprises as well as at small to medium-sized businesses Describes best practices and pragmatic approaches so readers can put them into action. Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources.