Managing Evolution of Heterogeneous Data Sources of a Data Warehouse

被引：0
|
作者：
Solodovnikova, Darja [1 ]
Niedrite, Laila [1 ]
Svilpe, Lauma [1 ]
机构：
[1] Univ Latvia, Fac Comp, Raina Blvd 19, Riga, Latvia
来源：
PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS (ICEIS 2021), VOL 1 | 2021年
关键词：
Data Warehouse; Evolution; Change Propagation; Metadata; Big Data;
D O I：
10.5220/0010496601050117
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The evolution of heterogeneous integrated data sources has become a topical issue as data nowadays is very diverse and dynamic. For this reason, novel methods are necessary to collect, store and analyze data from various data sources as efficiently as possible, while also handling changes in data structures that have occurred as a result of evolution. In this paper, we propose a solution to problems caused by evolution of integrated data sources and information requirements for the data analysis system. Our solution incorporates an architecture that allows to perform OLAP operations and other kinds of analysis on integrated big data and a mechanism for detecting and automatically or semi-automatically propagating changes occured in heterogeneous data sources to a data warehouse.
引用
收藏
页码：105 / 117
页数：13
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