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Data Quality Assessment: A Case Study of PT JAS Using TDQM Framework

机译:数据质量评估:使用TDQM框架PT JAS的案例研究

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The success of a company in increasing profits and managing loss risk is largely determined by data. Good quality data can improve the quality of decision making at the top management level. PT JAS is a financial company that manages risk. Of course to support good risk management needs to be supported by good quality of data sources. The aim of this research is to identify data dimensions, analyze and measure the quality of data. So that, it can be used as a support for the company's strategy in managing risk and understanding the current conditions of data quality. In measuring this data quality, the writer uses a total data quality management (TDQM) framework. TDQM provides a common framework for facilitating understanding in data improv approach through data quality management. The steps taken in measuring data quality are identification of data to be measured, determining the dimensions of data quality used, measurement of data quality, and then analyze the measurement results. From the measurement results, obtained factors that cause data quality problems, for example the pattern of imports of debtor data in large numbers. In addition, there are no policies related to data quality management and from some validation function errors in the system. Therefore, by measuring the quality of data and analyzing the causes, companies can find out in advance the condition of the quality of company data and immediately formulate strategies and steps in order to improve and develop the quality of the data they have, so that data can be a useful and valuable asset.
机译:公司在增加利润和管理损失风险方面的成功基本上由数据决定。优质数据可以提高最高管理水平的决策质量。 Pt Jas是一个管理风险的金融公司。当然要支持良好的风险管理,需要通过良好的数据来源来支持。本研究的目的是识别数据维度,分析和测量数据质量。这样,它可以用作公司管理风险和理解当前数据质量条件的策略的支持。在测量此数据质量时,作者使用全数据质量管理(TDQM)框架。 TDQM提供了一种常见的框架,可通过数据质量管理促进数据提升方法。测量数据质量采取的步骤是识别要测量的数据,确定使用的数据质量的尺寸,数据质量的测量,然后分析测量结果。从测量结果,获得导致数据质量问题的因素,例如大量债务数据的进口模式。此外,没有与数据质量管理有关的策略以及系统中的某些验证功能错误。因此,通过测量数据质量和分析原因,公司可以提前了解公司数据质量的条件,并立即制定策略和步骤,以提高他们拥有的数据的质量,使数据提高和发展数据可以是一个有用和有价值的资产。

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