| 書(shū)目名稱(chēng) | Data Cleaning | | 編輯 | Venkatesh Ganti,Anish Das Sarma | | 視頻video | http://file.papertrans.cn/263/262749/262749.mp4 | | 叢書(shū)名稱(chēng) | Synthesis Lectures on Data Management | | 圖書(shū)封面 |  | | 描述 | Data warehouses consolidate various activities of a business and often form the backbone for generating reports that support important business decisions. Errors in data tend to creep in for a variety of reasons. Some of these reasons include errors during input data collection and errors while merging data collected independently across different databases. These errors in data warehouses often result in erroneous upstream reports, and could impact business decisions negatively. Therefore, one of the critical challenges while maintaining large data warehouses is that of ensuring the quality of data in the data warehouse remains high. The process of maintaining high data quality is commonly referred to as data cleaning. In this book, we first discuss the goals of data cleaning. Often, the goals of data cleaning are not well defined and could mean different solutions in different scenarios. Toward clarifying these goals, we abstract out a common set of data cleaning tasks that often need to be addressed. This abstraction allows us to develop solutions for these common data cleaning tasks. We then discuss a few popular approaches for developing such solutions. In particular, we focus | | 出版日期 | Book 2013 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-01897-8 | | isbn_softcover | 978-3-031-00769-9 | | isbn_ebook | 978-3-031-01897-8Series ISSN 2153-5418 Series E-ISSN 2153-5426 | | issn_series | 2153-5418 | | copyright | Springer Nature Switzerland AG 2013 |
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