本文關鍵詞： 倉儲物流 數(shù)據(jù)倉庫 Kettle ETL　出處：《東華大學》2017年碩士論文　論文類型：學位論文

【摘要】：倉儲物流是貨物生產(chǎn)銷售的重要環(huán)節(jié)。隨著貿易自由化和電子商務的興起,物流企業(yè)快速發(fā)展,為提高倉庫管理效率,發(fā)掘更多的倉庫供應商客戶,合理配置資源并降低經(jīng)營成本,經(jīng)營者在制定經(jīng)營決策時需要分析倉儲物流過程的整個環(huán)節(jié)的數(shù)據(jù),然而在業(yè)務系統(tǒng)中的數(shù)據(jù)是按照業(yè)務過程進行組織的,處于孤立分散的狀態(tài)并不適用于數(shù)據(jù)的統(tǒng)計和分析。在倉儲物流系統(tǒng)上建立數(shù)據(jù)倉庫,按照用于決策分析的主題對不同系統(tǒng)中數(shù)據(jù)進行重新組織,為數(shù)據(jù)分析和數(shù)據(jù)挖掘提供有效的數(shù)據(jù)來源。本文根據(jù)某市物流業(yè)實際運營過程中對倉儲物流數(shù)據(jù)分析的業(yè)務需求設計數(shù)據(jù)倉庫。在明確數(shù)據(jù)倉庫的主題領域的基礎上設計數(shù)據(jù)倉庫的概念模型,并使用星型架構設計邏輯模型,根據(jù)不同的邏輯模型進行粒度分析和緩慢變更維的設計,最后設計索引和數(shù)據(jù)倉庫中的物理表完成數(shù)據(jù)倉庫的建立。設計ETL過程首先分析不同的數(shù)據(jù)源并設計數(shù)據(jù)采集的過程。從不同的數(shù)據(jù)源中抽取數(shù)據(jù)到數(shù)據(jù)倉庫中,在抽取過程中根據(jù)維度表的特點設計不同的增量抽取過程提高抽取效率。在緩沖數(shù)據(jù)域表中對數(shù)據(jù)進行清洗和表合并過程中的字段轉換最后完成事實表和維度表的加載過程。在文章的最后對數(shù)據(jù)倉庫的應用進行介紹。本論文設計和實現(xiàn)的數(shù)據(jù)倉庫已在倉儲物流運營中開始使用,為倉儲物流的決策分析提供各種統(tǒng)計數(shù)據(jù),實現(xiàn)資源的合理配置和倉庫貨物的有效管理,大大地降低企業(yè)的經(jīng)營成本。
[Abstract]:Warehousing logistics is an important link of goods production and sales. With the development of trade liberalization and e-commerce, logistics enterprises develop rapidly, in order to improve the efficiency of warehouse management, to explore more warehouse supplier customers. Reasonable allocation of resources and reduce operating costs, operators in making business decisions need to analyze the whole link of the warehousing logistics process data, but the data in the business system is organized according to the business process. The isolated and decentralized state is not suitable for the statistics and analysis of the data. The data warehouse is established on the warehouse logistics system, and the data in different systems are reorganized according to the topic used for decision analysis. To provide effective data sources for data analysis and data mining. This paper designs a data warehouse according to the business requirements of warehouse logistics data analysis during the actual operation of logistics industry in a certain city. The conceptual model of data warehouse is designed based on this. And using star architecture design logic model, according to different logical models for granularity analysis and slowly changing dimension design. Finally, the index and the physical tables in the data warehouse are designed to complete the establishment of the data warehouse. The ETL process is designed to analyze different data sources and design the process of data collection. Data are extracted from different data sources to the data warehouse. In the library. In the extraction process, different incremental extraction processes are designed according to the characteristics of dimension tables to improve the extraction efficiency. In the buffer data domain tables, the data are cleaned and the field conversion in the process of table merging is completed finally, the fact table and the dimension table are completed. At the end of the article, the application of data warehouse is introduced. The data warehouse designed and implemented in this paper has been used in warehouse logistics operation. This paper provides all kinds of statistical data for the decision analysis of warehouse logistics, realizes the rational allocation of resources and the effective management of warehouse goods, and greatly reduces the operating cost of enterprises.
【學位授予單位】：東華大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP311.13

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