標(biāo)題: Titlebook: Handbook of Data Quality; Research and Practic Shazia Sadiq Book 2013 Springer-Verlag Berlin Heidelberg 2013 data governance.data integrati [打印本頁(yè)] 作者: 重要 時(shí)間: 2025-3-21 16:14
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作者: Expurgate 時(shí)間: 2025-3-21 22:50 作者: Inclement 時(shí)間: 2025-3-22 03:43
The British Nutrition Foundation frameworks were applied to meet their organizations’ specific needs, environments, and cultures. Readers should come away from the chapter understanding the foundation behind the execution of data quality projects, the development of data quality programs, and generate ideas for incorporating data 作者: 粉筆 時(shí)間: 2025-3-22 08:26
Unsaturated Soils: Experimental Studiesucts, North America, is presented to explore the research question as to how Data Governance effectiveness can be measured as the ratio of the number of preventive data quality management (DQM) measures to the total number of DQM measures in order to trace the evolution of Data Governance over time.作者: olfction 時(shí)間: 2025-3-22 11:58 作者: Arboreal 時(shí)間: 2025-3-22 16:26
https://doi.org/10.1007/978-3-642-73756-5ribe a novel approach that considers . between data sources in truth discovery. Intuitively, if two data sources provide a large number of common values and many of these values are unlikely to be provided by other sources (e.g., particular false values), it is very likely that one copies from the o作者: 洞察力 時(shí)間: 2025-3-22 19:51 作者: liposuction 時(shí)間: 2025-3-22 21:41
On the Evolution of Data Governance in Firms: The Case of Johnson & Johnson Consumer Products North ucts, North America, is presented to explore the research question as to how Data Governance effectiveness can be measured as the ratio of the number of preventive data quality management (DQM) measures to the total number of DQM measures in order to trace the evolution of Data Governance over time.作者: 努力趕上 時(shí)間: 2025-3-23 01:35
Managing Quality of Probabilistic Databasese queries) and (2) queries that require the knowledge of the relative ranking of the tuples (e.g., . queries). We then propose a polynomial-time solution to achieve an optimal improvement in PWS-quality. Other fast heuristics are also examined.作者: modest 時(shí)間: 2025-3-23 06:37 作者: fatuity 時(shí)間: 2025-3-23 10:06
https://doi.org/10.1007/978-3-642-36257-6data governance; data integration; data provenance; data quality; data warehouses; database management; du作者: 刀鋒 時(shí)間: 2025-3-23 14:05
Shazia SadiqPresents a comprehensive framework based on organizational, architectural, and computational techniques and solutions.Includes a separate section devoted to successful data quality approaches in indus作者: 過(guò)時(shí) 時(shí)間: 2025-3-23 21:29 作者: 頌揚(yáng)國(guó)家 時(shí)間: 2025-3-24 01:22 作者: Sputum 時(shí)間: 2025-3-24 06:03 作者: MIR 時(shí)間: 2025-3-24 08:03
Prologue: Research and Practice in Data Quality Management,alth of knowledge on data quality research and practice. The chapter presents a snapshot of these contributions from both research and practice, and highlights the background and rational for the handbook.作者: 粗野 時(shí)間: 2025-3-24 12:53
Generic and Declarative Approaches to Data Quality Management been applicable to specific problems and domains. In the last few years we have seen the emergence of more generic solutions, and also of declarative and rule-based specifications of the intended solutions of data cleaning processes. In this chapter we review some of those recent developments.作者: 凝結(jié)劑 時(shí)間: 2025-3-24 17:45 作者: ciliary-body 時(shí)間: 2025-3-24 22:02
https://doi.org/10.1007/978-3-031-16284-8alth of knowledge on data quality research and practice. The chapter presents a snapshot of these contributions from both research and practice, and highlights the background and rational for the handbook.作者: 后來(lái) 時(shí)間: 2025-3-25 00:37
Unsaponifiable Matter in Plant Seed Oilsly work with a terrific team of researchers and business people at Bell Labs and AT&T; constant reflection on the meanings and methods of quality, the strange and wondrous properties of data, the importance of data and data quality in markets and companies, and the underlying reasons that some enter作者: Embolic-Stroke 時(shí)間: 2025-3-25 04:28 作者: Anemia 時(shí)間: 2025-3-25 07:36 作者: 錫箔紙 時(shí)間: 2025-3-25 13:51 作者: Pruritus 時(shí)間: 2025-3-25 16:58
Wojciech T. So?owski,Scott W. Sloanuses (as compared to transactional databases) include data integration from multiple sources and emphasis on temporal, historical, and multidimensional data. In this chapter, we survey data warehouse quality problems and solutions, including data freshness (ensuring that materialized views are up to作者: 形狀 時(shí)間: 2025-3-25 23:38 作者: 社團(tuán) 時(shí)間: 2025-3-26 01:43
https://doi.org/10.1057/9780230249158ase in the number and complexity of data quality problems. Data glitches, a common name for data quality problems, can be simple and stand alone, or highly complex with spatial and temporal correlations. In this chapter, we provide an overview of a comprehensive and measurable data quality process. 作者: 巨碩 時(shí)間: 2025-3-26 06:52
Detailliertes Screening im 1. Trimester been applicable to specific problems and domains. In the last few years we have seen the emergence of more generic solutions, and also of declarative and rule-based specifications of the intended solutions of data cleaning processes. In this chapter we review some of those recent developments.作者: LUDE 時(shí)間: 2025-3-26 09:17 作者: glowing 時(shí)間: 2025-3-26 15:02 作者: 母豬 時(shí)間: 2025-3-26 19:24
https://doi.org/10.1007/978-3-662-67635-6ese applications, . can be used to store uncertain data, and querying facilities are provided to yield answers with statistical confidence. Given that a limited amount of resources is available to “clean” the database (e.g., by probing some sensor data values to get their latest values), we address 作者: 突變 時(shí)間: 2025-3-26 21:29
https://doi.org/10.1007/978-3-642-73756-5uire integrating data from multiple sources. Each of these sources provides a set of values, and different sources can often provide conflicting values. To present quality data to users, it is critical to resolve conflicts and discover values that reflect the real world; this task is called .. Typic作者: left-ventricle 時(shí)間: 2025-3-27 01:38
Ronald S. Illingworth,Rupert Maria Kohl highlights the Canadian experience in the capture and use of health information including a brief introduction to the Canadian health care system and the Canadian Institute for Health Information (CIHI); an overview of CIHI strategies and programs that support quality health information for key sta作者: itinerary 時(shí)間: 2025-3-27 05:18 作者: Cardioversion 時(shí)間: 2025-3-27 09:34
Prologue: Research and Practice in Data Quality Management,alth of knowledge on data quality research and practice. The chapter presents a snapshot of these contributions from both research and practice, and highlights the background and rational for the handbook.作者: 昆蟲(chóng) 時(shí)間: 2025-3-27 13:38
Data Quality Management Past, Present, and Future: Towards a Management System for Dataly work with a terrific team of researchers and business people at Bell Labs and AT&T; constant reflection on the meanings and methods of quality, the strange and wondrous properties of data, the importance of data and data quality in markets and companies, and the underlying reasons that some enter作者: Anguish 時(shí)間: 2025-3-27 21:27 作者: hypnotic 時(shí)間: 2025-3-27 22:34
Cost and Value Management for Data Qualityvalue are rare and indeed difficult to develop. At the same time, as a critical concern to the success of organizations, the cost and value of data quality become important. Numerous business initiatives have been delayed or even cancelled, citing poor-quality data as the main concern. Previous rese作者: 自由職業(yè)者 時(shí)間: 2025-3-28 03:50 作者: Fierce 時(shí)間: 2025-3-28 08:29 作者: CHOIR 時(shí)間: 2025-3-28 11:23 作者: 得體 時(shí)間: 2025-3-28 16:51
Data Glitches: Monsters in Your Dataase in the number and complexity of data quality problems. Data glitches, a common name for data quality problems, can be simple and stand alone, or highly complex with spatial and temporal correlations. In this chapter, we provide an overview of a comprehensive and measurable data quality process. 作者: 消耗 時(shí)間: 2025-3-28 19:04
Generic and Declarative Approaches to Data Quality Management been applicable to specific problems and domains. In the last few years we have seen the emergence of more generic solutions, and also of declarative and rule-based specifications of the intended solutions of data cleaning processes. In this chapter we review some of those recent developments.作者: overhaul 時(shí)間: 2025-3-29 01:03
Linking Records in Complex Context etc. In this chapter, we focus on techniques that enable record linkage in so-called complex context, which includes data sets with hierarchial relations, data sets that contain temporal information, and data sets that are extracted from the Web. For each method, we describe the problem to be solve作者: 緩和 時(shí)間: 2025-3-29 03:45
A Practical Guide to Entity Resolution with OYSTERand support master data management programs. The chapter is organized into two main parts. The first part discusses the components of ER with particular emphasis approximate matching algorithms and the activities that comprise identity information management. The second part provides a step-by-step 作者: Barrister 時(shí)間: 2025-3-29 10:49 作者: 摘要記錄 時(shí)間: 2025-3-29 13:48 作者: 委屈 時(shí)間: 2025-3-29 16:55
Ensuring the Quality of Health Information: The Canadian Experience highlights the Canadian experience in the capture and use of health information including a brief introduction to the Canadian health care system and the Canadian Institute for Health Information (CIHI); an overview of CIHI strategies and programs that support quality health information for key sta作者: arthroscopy 時(shí)間: 2025-3-29 21:19 作者: Prostaglandins 時(shí)間: 2025-3-30 01:51 作者: 啟發(fā) 時(shí)間: 2025-3-30 05:04 作者: Obstruction 時(shí)間: 2025-3-30 08:24
Die Fü?e – Sicherheit und Stabilit?tues to their own environment. A unified global approach to data quality remained elusive until the new millennium. This chapter describes Shell’s global data quality journey since the early part of the millennium to the present.作者: 過(guò)份好問(wèn) 時(shí)間: 2025-3-30 14:37
