本文選題：數(shù)據(jù)倉(cāng)庫(kù)　切入點(diǎn)：維度建模　出處：《首都師范大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：財(cái)務(wù)管理作為國(guó)內(nèi)首先實(shí)現(xiàn)計(jì)算管理的領(lǐng)域,積累了大量數(shù)據(jù),是管理的財(cái)富,對(duì)這些數(shù)據(jù)的分析有重要的意義。傳統(tǒng)的基于數(shù)據(jù)庫(kù)技術(shù)的決策支持系統(tǒng)由于其技術(shù)弱且缺少統(tǒng)一性,無(wú)法處理大量的數(shù)據(jù)且應(yīng)用復(fù)雜,已無(wú)法滿足用戶的需要。數(shù)據(jù)倉(cāng)庫(kù)技術(shù)和聯(lián)機(jī)分析處理(OLAP)技術(shù)的出現(xiàn)為大數(shù)據(jù)的處理帶來(lái)了希望,也解決了傳統(tǒng)的決策支持系統(tǒng)的問(wèn)題。 數(shù)據(jù)倉(cāng)庫(kù)技術(shù)為決策支持系統(tǒng)的數(shù)據(jù)存儲(chǔ)和管理提供了解決方法,但數(shù)據(jù)的原始記錄一般存儲(chǔ)在不同的數(shù)據(jù)庫(kù)和源文件中,這也使得原始數(shù)據(jù)直接導(dǎo)入到數(shù)據(jù)倉(cāng)庫(kù)是不切實(shí)際的。因此,首先我們要為數(shù)據(jù)倉(cāng)庫(kù)的構(gòu)建建立模型,然后在設(shè)置的模型的基礎(chǔ)上設(shè)計(jì)抽取工具,通過(guò)數(shù)據(jù)抽取、轉(zhuǎn)換和加載(ETL)這一過(guò)程將源數(shù)據(jù)庫(kù)中的數(shù)據(jù)裝載到目標(biāo)數(shù)據(jù)庫(kù)中。ETL是構(gòu)建數(shù)據(jù)倉(cāng)庫(kù)的重要組成部分。ETL這一過(guò)程需要解決如主題的分散、數(shù)據(jù)重復(fù)、同一對(duì)象的命名方式或表達(dá)方式不一致的現(xiàn)象等問(wèn)題。 隨著計(jì)算機(jī)技術(shù)的快速發(fā)展,數(shù)據(jù)倉(cāng)庫(kù)技術(shù)也得以快速發(fā)展以及廣泛的應(yīng)用。本文基于某機(jī)關(guān)單位的總賬信息管理系統(tǒng)和非稅信息管理系統(tǒng),詳述了數(shù)據(jù)倉(cāng)庫(kù)的維度建模和ETL工具的設(shè)計(jì)。 本文采用維度建模作為其建模策略,結(jié)合總賬和非稅管理項(xiàng)目,主要探討了維度建模設(shè)計(jì)問(wèn)題,其中包括事實(shí)表和維度表的設(shè)計(jì),通過(guò)星型模型來(lái)進(jìn)行維度建模。首先介紹了維度建模的理論基礎(chǔ),結(jié)合具體的項(xiàng)目來(lái)進(jìn)行維度模型的設(shè)計(jì)。 ETL是構(gòu)建數(shù)據(jù)倉(cāng)庫(kù)這一過(guò)程最重要的設(shè)計(jì)。首先介紹了ETL的結(jié)構(gòu)及這一過(guò)程元數(shù)據(jù)的重要性。然后具體結(jié)合總賬抽取工具和報(bào)表抽取工具,詳述了基于元數(shù)據(jù)的ETL過(guò)程的設(shè)計(jì)。
[Abstract]:Financial management, as the first field to realize calculation management in China, has accumulated a lot of data and is the wealth of management. The analysis of these data is of great significance. Because of its weak technology and lack of unity, traditional decision support system based on database technology is unable to deal with a large number of data and its application is complex. The emergence of data warehouse technology and on-line analytical processing (OLAP) technology brings hope to big data's processing and solves the problem of traditional decision support system. Data warehouse technology provides a solution for data storage and management in decision support systems, but the original records of data are generally stored in different databases and source files. This also makes it impractical to import raw data directly into the data warehouse. So, first of all, we have to model the construction of the data warehouse, and then we design the extraction tool based on the set model. The process of loading data from the source database into the target database. ETL is an important component of building a data warehouse. Problems such as inconsistent naming or expression of the same object. With the rapid development of computer technology, data warehouse technology has been rapidly developed and widely used. This paper is based on the general ledger information management system and non-tax information management system. The dimension modeling of data warehouse and the design of ETL tool are described in detail. In this paper, dimension modeling is used as its modeling strategy, and combined with general ledger and non-tax management project, dimension modeling design is mainly discussed, including fact table and dimension table design. Firstly, the theoretical basis of dimension modeling is introduced, and the design of dimension model is carried out with specific items. ETL is the most important design in the process of building data warehouse. Firstly, the structure of ETL and the importance of metadata are introduced. Then, the design of ETL process based on metadata is described in detail by combining general ledger extraction tool and report extraction tool.
【學(xué)位授予單位】：首都師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP311.13;F233

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