OLAP和数据挖掘技术在QAD产品审计中的应用与分析研究 .docx
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1、精品名师归纳总结OLAP 和数据挖掘技术在QAD 产品审计中的应用与争论摘要随着时代的进展,如今的企业已大多进入了“无纸化”的办公时代。原有的手工信息输入与分析已无法适应如今日益增多的信息数据。可以说,企业每天都面临着大量的商业信息,而如何利用、分析好这些数据从而为企业的进展供应指导就显得特殊重要。对于QAD公司而言,它是一家特的为制造业供应企业解决方案的软件供应商,它在全球范畴内的九十多个国家拥有超过六千多个客户。每一年,它都会对每个客户使用公司软件产品的情形进行审计。在每个客户审计的过程中,自然会产生大量的数据。对于公司而言,全部客户的审计数据将是百万级的。面对如此巨大的数据,如何从这些数
2、据中猎取公司所需的信息,分析出审计的结果,并得出肯定的指导性结论就显得特殊重要。为此,本文提出了一种基于联机分析处理(OLAP )和数据挖掘技术的审计信息分析的设计。 OLAP和数据挖掘技术是近年来数据库领域和人工智能领域争论的热点,它通过对大量数据进行分析和处理,得到隐含在这些数据背后有用的信息和学问。本工程实现了基于 SQL Server 2021 分析服务( SSAS)在审计信息立方体之上的OLAP 多维数据分析和MDX多维数据查询,并利用决策树、神经网络等数据挖掘算法对审计信息数据进行挖掘,得出有用的学问。为实现上述目标,第一需要打算储备分析后的审计信息的数据库版本与类型以及最终生成审
3、计结果报表所需使用的报表生成工具。为此,针对数据库的挑选提出了以下几种可行的解决方案: Progress 数据库、 MySQL数据库、 Access 数据库和SQL Server 数据库。依据实际需求,分别比较了以上四种数据库的优缺点,最终权衡之后挑选了SQL Server 数据库作为本工程的关系数据库服务器。同样,针对报表生成工具,也提出了以下几种可行的解决方案: QAD公司自己实现的报表生成框架、微软的Access 工具和微软的 Excel 工具。分析了以上几种工具使用的便利性以及代价考虑,最终挑选了大家比较常用且比较轻量型的 Excel 作为我们最终的报表生成工具。在选定了数据库和报表生
4、成工具的解决方案之后,便要对历史审计数据进行肯定的整理、分析以及数据提取和储备工作。审计数据是由公司产品所供应的功能菜单运行后自动生成的,客户在对这些多种多样的报表整理时,可能依据自身的习惯进行不同的打包方 式。因此公司从客户手上得到的审计数据结构就是复杂繁多的,没有肯定的规律性可循, 这对我们进行历史审计信息的提取造成了肯定的困难与阻碍。经过对历史审计数据的具体分析之后,找到了所需要的两个审计文件:应用使用具体报告和许可权使用情形报告。其他诸如数据库使用报告等日志文件目前对我们来说并没有太大的意义。因此我们的目标只是在每个客户的审计数据文件夹下找到这两个文件,分析提取数据,并存入数据库中。在
5、实践中,发觉假如不对历史数据进行处理,直接运行数据分析提取程序,就效率特别低 下。究其缘由是由于程序每次都需要遍历每个文件来确认该文件是否为所需的那两个报告文件,因此要花费大量的时间。为解决这一问题,就需要在程序之上再加上一层数据预处理的程序,即将不需要的历史数据文件过滤,依据原有的目录结构,只留下所需的那两个文件。这样,在数据预处理的基础上,程序运行的效率将大大提高。解决了这一问题之 后,便是要将分析出的数据存入数据库中。依据历史审计数据信息及相关的外部数据信息,依据需求,共设计了六张数据表。该数据库将为后面的OLAP 供应高效的数据源。有了关系数据库源,便可利用SSAS 对审计数据进行维度
6、建模。本文重点论述了审计可编辑资料 - - - 欢迎下载精品名师归纳总结信息数据的概念模型设计和规律模型设计,包括度量、维度和粒度的设计,事实表和维表的设计,同时采纳了雪花模型构造了规律视图,最终生成了审计信息的多维立方体,供最终生成审计结果报表和数据挖掘供应了多维数据源,完成了OLAP 在 QAD 产品审计中的应用。在生成审计结果报表时,使用Excel 中的透视表,建立数据库连接,挑选建立的多维数据源,便可读取多维数据中的内容。为了便利客户批阅,特殊定义了十多个报表模板,可供客户挑选,基本涵盖了全部的审计结果,且客户可以自主挑选想要查看的内容, 对数据进行肯定的钻取等,特别便利。最终,便是使
7、用数据挖掘技术对审计数据进行肯定的挖掘任务争论。传统的数据挖掘过程往往基于关系数据库。本文探讨了基于OLAP 的数据挖掘技术在产品审计中的应用, 分别使用了决策树算法和神经网络算法对同一个挖掘模型进行了挖掘,并利用提升图比较了两个算法的挖掘精确性。本文所建立的挖掘模型为分析客户挑选QAD公司不同产品类型组合的因素,意在发觉一个行业领域内使用QAD公司产品组合的正确实践,为不同的 客户在挑选公司产品组合时供应肯定的建议。由于时间及精力的有限,只是粗略探究了数据挖掘在公司审计中应用的可能性。信任可以利用该技术挖掘出更多对公司经营决策有指导性意义的学问。本文的争论和结果说明,OLAP 和数据挖掘技术
8、在QAD 公司产品审计中的应用是可行的,而且是便利高效的。它不仅从企业治理的角度为公司决策层与销售人员供应了更为智能的分析方法和途径,仍为审计分析人员供应了新的手段和视角,来挖掘出更多数据背后隐匿的有用的学问。关键词: 数据挖掘, OLAP ,多维数据分析,SQL Server 2021 分析服务,产品审计THE APPLICATION AND RESEARCH OF OLAP AND DATA MINING TECHNOLOGY INQAD PRODUCT AUDITABSTRACTWiththe development of the society, science and technol
9、ogy, most ofthe enterprises have now entered the paperless office time. The original manual input and analysis couldnt deal with the increasing information and data any more. Every day, enterprises are faced with lots of business information, and be aware of know how to use these data to analysis, t
10、o provide guidance for development of the enterprise is especially important.For QAD which is a software supplier company who provides solutions to specialized manufacturing enterprises, has more than 6,000 multiple clients within 90 countries worldwide. Every year, all clientsusing software product
11、s conditions willbe audited by the company. In every customer audit process, large amounts of data will be produced. For QAD, the number of all customersaudit data gathered together will be millions. Facing such large numbers of data, it is especially important to know how to get the information the
12、 company need, to analysis the audit results, and some guidance conclusions from this huge and messy data.Therefore, this paper proposed a multi-dimensional analysis of QAD product auditing design based on OLAP and data mining technology. OLAP and data mining technology have becominga research hot s
13、pot of database and the field of artificial可编辑资料 - - - 欢迎下载精品名师归纳总结intelligence during recent years. It through the large data analysis and processing, implicates useful information and knowledge behind these data. This project realized OLAP multi-dimensional data analysis and MDXmulti-dimensional d
14、ata query on the basis of SQL Server Analysis Service 2021 in the audit information cube, and achieved audit information data mining using decision trees and the neural network data miningalgorithm foraudit informationto draw useful knowledge forthe company.To achieve this goal, we first need to dec
15、ide the databaseversion and type to choose, which is used to store the audit information after the analysis and which reporting framework tools to choose to generate final audit result report. Therefore, several feasible solutions of databases based on demand were put forward. They are Progress data
16、base, MySQLdatabase,Access database and SQL Server database. According to actual needs, and after comparing each advantages and disadvantages of the above four database servers, the SQL server database was chosen as the relational database server finally. Similarly, for reporting tools, the followin
17、g feasible solutions were also put forward:QADreportingframeworkrealized bythe company, Microsoft Access tool and Microsoft Excel tools. Excel was chosen as the reporting toolfinally becausemost of the users are very familiar with it and it is powerfulfor generating various reports though it is very
18、 lightweight.After finished selection of database and report generation tool, the next step was to deal with the audit data. We need to sort out, analysis and extract data and finally make these useful information be stored in database correctly. Audit data is automatic generated by using the produc
19、t function menu. Customer will work on these various reports according to their own habit of different packaging. So the company obtained from the customer on the audit data structure is complex range, no certain regularity, this to our historical audit information extraction has caused some difficu
20、lties and obstacles. Through analyzing the historical data after detailed analysis of audit, we found out that only two kinds of report are needed, includingApplication Detail Usage Profile Report and Licensed Application Report. Other files such as database log files are not so important to us for
21、now. So our goal is to find out these two files in each customer audit data folder and to analysis, extract data from these two files and store the extracted information in database. In practice, we found that ifwe run data processing procedure directly instead of pre-processing the historical data
22、first, then the data processing procedures efficiency is very low. The reason it that every time the procedure is run, it need to traversal every file in the appointed folders to see whether this file is useful for us or not, that is to say the procedure will open each file to see whether this file
23、is the ApplicationDetailUsage ProfileReportand Licensed Application Report or not, thus a lot of time is spent. To solve this problem, it need to plus a layer of data pretreatment process before the above processing procedures.That is to say, after running the data pretreatment process, some histori
24、cal audit files which are not needed will be filtered, only two kinds of report mentioned above will be remained according to the original directory structure. So, on the basis of data pretreatment, the program will greatly improve the efficiency of the operation. Aftersolving this problem successfu
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