The Experts below are selected from a list of 927 Experts worldwide ranked by ideXlab platform
Edward T Chen - One of the best experts on this subject based on the ideXlab platform.
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Implementation Issues of Enterprise Data Warehousing and Business Intelligence in the Healthcare Industry.
Communications of the IIMA, 2012Co-Authors: Edward T ChenAbstract:The healthcare industry is following the lead of other industries and finding value in Enterprise Data Warehousing (EDW) and business intelligence (BI) tools. Healthcare organizations are leveraging these tools to provide a plethora of benefits realized through enhanced business operations and performance. The EDW combines Data from multiple source systems across an Enterprise, and BI tools extract the Data in meaningful ways to enable managers to make the best informed decisions. As with all management information systems, there are technical issues to be considered that impact the design, build, implementation, and support of the system. These benefits and challenges are explored, as well as special considerations necessary for the healthcare industry compared to other industries utilizing Data Warehousing and business intelligence. This paper investigates these critical issues and provides suggestions to harness the implementation of EDW and BI in the healthcare industry. [ABSTRACT FROM AUTHOR]
Wang Li - One of the best experts on this subject based on the ideXlab platform.
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an object oriented framework for Data quality management of Enterprise Data warehouse
Lecture Notes in Computer Science, 2006Co-Authors: Wang LiAbstract:Enterprise Data Warehousing technology aims at providing integrated, consolidated and historical Data for users to analyze businesses and make decisions. In order to obtain the correct results, the high Data quality is required. In this paper, we analyze the quality problems of Enterprise Data warehouse and present an object-oriented framework for Data quality management. In this framework, an object-oriented Data quality model (OODQM) is built. The Data quality requirements, the participators, the Data quality checking object, and the possible Data quality problems, form the core components of OODQM. The method we provide is a goal-driven method. Once the Data quality goal is built, we manage Data quality by the interaction of those components of OODQM.
Alan Simon - One of the best experts on this subject based on the ideXlab platform.
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Enterprise Business Intelligence and Data Warehousing
Morgan Kaufmann, 2019Co-Authors: Alan SimonAbstract:Corporations and governmental agencies of all sizes are embracing a new generation of Enterprise-scale business intelligence (BI) and Data Warehousing (DW), and very often appoint a single senior-level individual to serve as the Enterprise BI/DW Program Manager. This book is the essential guide to the incremental and iterative build-out of a successful Enterprise-scale BI/DW program comprised of multiple underlying projects, and what the Enterprise Program Manager must successfully accomplish to orchestrate the many moving parts in the quest for true Enterprise-scale business intelligence and Data Warehousing. Author Alan Simon has served as an Enterprise business intelligence and Data Warehousing program management advisor to many of his clients, and spent an entire year with a single client as the adjunct consulting director for a $10 million Enterprise Data Warehousing (EDW) initiative. He brings a wealth of knowledge about best practices, risk management, organizational culture alignment, and other Critical Success Factors (CSFs) to the discipline of Enterprise-scale business intelligence and Data Warehousing
Bill Oconnell - One of the best experts on this subject based on the ideXlab platform.
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building an information on demand Enterprise that integrates both operational and strategic business intelligence
International Conference on Electronic Commerce, 2007Co-Authors: Bill OconnellAbstract:The talk will discuss existing market directions driving the development and integration of Business Process Management (PBM), Corporate Performance Management (CPM), as well as strategic Business Intelligence analysis into a holistic Enterprise architecture. In doing so, Enterprise architectural approaches will be outlined with the integration of Information services provided to the application Business Processes for both B2B and B2C. Furthermore, Architectural approaches for integrating real-time Enterprise Data Warehousing, Master Data Management, Content and Discovery systems holistically into operational analytics will be discussed. This approach demands metaData integration as well as simplify operational Business Intelligence through embedded analytics within day-to-day business processes. Information as a Service (IaaS) as well as Service Oriented Architecture (SOA) are tooling and approaches to accomplish this.
Gary Nolan - One of the best experts on this subject based on the ideXlab platform.
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efficient sap netweaver bi implementation and project management
2007Co-Authors: Gary NolanAbstract:The challenges facing BI/BW projects can be cultural, political, technical, or fiscal in nature. This book helps you navigate past a wide range of potential pitfalls to ensure a largely problem-free BW implementation. Using a lessons-learned approach, the author highlights critical BW project-related issues from the start of an implementation to the end. Readers discover how to eliminate problems before they occur, by preparing for them from the outset. Learn about common BW mistakes, find out how to avoid them and understand how successful BW projects can be executed. Readers of this comprehensive reference get unparalleled advice to run your BW project efficiently, while circumventing major delays and common stumbling blocks. In addition, you'll benefit from the experience of others via sample documents such as review checklists, communications documents, and landscape and architecture documents. This book is highly valuable for those implementing BI NetWeaver 2004s (7.0) as well as 3.x. Highlights: Enterprise Data Warehousing Data Quality Scope Management Risk Analysis Data Modeling Transport Management Change Management ABAP Standards
