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This volume includes the papers presented at the 24th International Conference on Information Integration and Web Intelligence (iiWAS 2022), organized in conjunction with 24th International Conference on Advances in Mobile Computing & Multimedia Intelligence (MoMM2022). ​The dominant research focus of submitted papers was artificial intelligence and machine learning. The accepted papers presented advances and innovations in an array of areas such as internet of things, virtual and augmented reality, various business applications. iiWAS 2022 attracted 97 papers, from which the Program Committee selected 26 regular papers and 25 short papers. Due to safety concerns as well as other restrictions preventing travel and gatherings, it was decided to organize iiWAS 2022 as a virtual conference.
This book constitutes the refereed conference proceedings of the 25th International Conference on Information Integration and Web Intelligence, iiWAS 2023, organized in conjunction with the 21st International Conference on Advances in Mobile Computing and Multimedia Intelligence, MoMM2023, held in Denpasar, Bali, Indonesia, during December 4-6, 2023. The 24 full papers and 24 short papers presented in this book were carefully reviewed and selected from 96 submissions. The papers are divided into the following topical sections: business data and applications; data management; deep and machine Learning; generative AI; image data and knowledge graph; recommendation systems; similarity measure and metric; and topic and text matching.
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.
Annotation In this book, Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects.
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.
Business professionals who want to advance their careers need to have a strong understanding of how to utilize business intelligence. This new book provides a comprehensive introduction to the basic business and technical concepts they’ll need to know. It integrates case studies that demonstrate how to apply the material. Business professionals will also find suggested further readings that will develop their knowledge and help them succeed.
Data warehousing and knowledge discovery are increasingly becoming mission-critical technologies for most organizations, both commercial and public, as it becomes incre- ingly important to derive important knowledge from both internal and external data sources. With the ever growing amount and complexity of the data and information available for decision making, the process of data integration, analysis, and knowledge discovery continues to meet new challenges, leading to a wealth of new and exciting research challenges within the area. Over the last decade, the International Conference on Data Warehousing and Knowledge Discovery (DaWaK) has established itself as one of the most important international scientific events within data warehousing and knowledge discovery. DaWaK brings together a wide range of researchers and practitioners working on these topics. The DaWaK conference series thus serves as a leading forum for discu- ing novel research results and experiences within data warehousing and knowledge th discovery. This year’s conference, the 11 International Conference on Data Wa- housing and Knowledge Discovery (DaWaK 2009), continued the tradition by d- seminating and discussing innovative models, methods, algorithms, and solutions to the challenges faced by data warehousing and knowledge discovery technologies.
Implementing business intelligence is a strategic activity that channels the outcomes of performance throughout the healthcare organization and its stakeholders. Additionally, business intelligence provides a visual, high-level view of historical trends, current operations and predictive analysis. Through insightful chapters written by industry experts and numerous, real-world case studies, this book demonstrates myriad practical and proven steps to developing a business intelligence solution, including pre- and post-implementation issues. This book is packed with information that will help you and your organization raise awareness of hidden business intelligence, generate improved analytical data and spread the access to this new information across the continuum of care. 2012.
The definitive book and eBook guide to Oracle information integration and migration in a heterogeneous world.
Open Source Data Warehousing and Business Intelligence is an all-in-one reference for developing open source based data warehousing (DW) and business intelligence (BI) solutions that are business-centric, cross-customer viable, cross-functional, cross-technology based, and enterprise-wide. Considering the entire lifecycle of an open source DW &