Entity Resolution and Master Data Life Cycle Management in the Era of Big Data
نویسنده
چکیده
Proper management of master data is a critical component of any enterprise information system. However, effective master data management (MDM) requires that both IT and Business understand the life cycle of master data and the fundamental principles of entity resolution (ER). This paper provides a high-level overview of current practices in data matching, record linking, and entity information life cycle management that are foundational to building an effective strategy to improve data integration and MDM. These include the need for ongoing ER analytics that systematically and quantitatively measure ER performance, investing in clerical review and asserted resolution for continuous improvement, and addressing the large-scale ER challenge through distributed processing.
منابع مشابه
Entity identity information management (EIIM)
This paper introduces and defines the concept of entity identity information management (EIIM). EIIM is a component of entity identity management (EIM) that utilizes data structures, data integration, and entity resolution (ER) methods and algorithms in order to maintain entity identity integrity, a goal that EIIM shares with master data management (MDM). The paper also explores some of the des...
متن کاملP-V-L Deep: A Big Data Analytics Solution for Now-casting in Monetary Policy
The development of new technologies has confronted the entire domain of science and industry with issues of big data's scalability as well as its integration with the purpose of forecasting analytics in its life cycle. In predictive analytics, the forecast of near-future and recent past - or in other words, the now-casting - is the continuous study of real-time events and constantly updated whe...
متن کاملThe Effect of Transitive Closure on the Calibration of Logistic Regression for Entity Resolution
This paper describes a series of experiments in using logistic regression machine learning as a method for entity resolution. From these experiments the authors concluded that when a supervised ML algorithm is trained to classify a pair of entity references as linked or not linked pair, the evaluation of the model’s performance should take into account the transitive closure of its pairwise lin...
متن کاملEffect of Firm Life Cycle Theory on the relevance of Risk Measures
Risk phenomenon is one of the key characteristics of decision making in the fields of investment, issues associated with financial markets, and various economic activities. The present study was an attempt to evaluate the impact of different periods of life cycle of companies on the relevance of risk measures of companies. In this study, the collected data have been analyzed in three stages. Fi...
متن کاملBig Data Quality: From Content to Context
Over the last 20 years, and particularly with the advent of Big Data and analytics, the research area around Data and Information Quality (DIQ) is still a fast growing research area. There are many views and streams in DIQ research, generally aiming at improving the effectiveness of decision making in organizations. Although there are a lot of researches aimed at clarifying the role of BIG data...
متن کامل