Quality Assessment of Data Using Statistical and Machine Learning Methods

被引：8
|
作者：
Singh, Prerna [1 ]
Suri, Bharti [2 ]
机构：
[1] Jagan Inst Management Studies, New Delhi, India
[2] USICT, New Delhi, India
来源：
COMPUTATIONAL INTELLIGENCE IN DATA MINING, VOL 2 | 2015年 / 32卷
关键词：
Conceptual model; Data warehouse quality; Multidimensional data model; Statistical; Understand ability; CONCEPTUAL MODELS; METRICS;
D O I：
10.1007/978-81-322-2208-8_10
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Data warehouses are used in organization for efficiently managing the information. The data from various heterogeneous data sources are integrated in data warehouse in order to do analysis and make decision. Data warehouse quality is very important as it is the main tool for strategic decision. Data warehouse quality is influenced by Data model quality which is further influenced by conceptual data model. In this paper, we first summarize the set of metrics for measuring the understand ability of conceptual data model for data warehouses. The statistical and machine learning methods are used to predict effect of structural metrics, on understand ability, efficiency and effectiveness of Data warehouse Multidimensional (MD) conceptual model.
引用
收藏
页码：89 / 97
页数：9
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