Understanding  Record Linkage

Record linkage, also known as entity resolution, data linking or identity stitching, is a powerful technique that transforms raw data into actionable insights. In essence, it involves identifying and matching related data across multiple sources to create a unified view of an individual or entity.

Record linkage is used across industries, from finance and healthcare to marketing and government. Its applications include fraud detection, customer profiling, patient monitoring, and more.

So what exactly is record linkage? What are its benefits? And how does it work? In this post, we answer the most popular questions about record linkage.

What is Record Linkage?

Record linkage is the process of identifying and connecting related data points from disparate sources. This can involve matching data based on various attributes such as name, address, age, gender and more.

Why is Record Linkage Important?

Record linkage enables organizations to gain more accurate insights into their data by eliminating duplications and inconsistencies. This leads to better decision-making and improved outcomes.

How Does Record Linkage Work?

Record linkage uses algorithms to compare large datasets for similarities in specific attributes. Once matches are found, additional techniques such as fuzzy matching or probabilistic matching can be applied to refine results.

What are the Key Benefits of Record Linkage?

The benefits of record linkage include improved accuracy, increased efficiency in managing data, faster decision-making based on reliable information.

Who Uses Record Linkage?

Record linkage is used by various organizations across industries such as healthcare providers, financial institutions, government agencies and marketers.

What are the Challenges with Record Linkage?

Challenges with record linkage can include imperfect data quality, variations in how different sources define attributes such as name or address; privacy concerns around linking sensitive information.

What Tools are Available for Record Linkage?

There are many tools available for record linkage including open-source software like Python's recordlinkage library, as well as proprietary solutions like IBM's InfoSphere MDM.

Record linkage is a critical technique for any organization that wants to harness the power of data. By connecting disparate datasets, it unlocks new insights and opportunities to optimize processes and improve outcomes.

References:

  1. Fellegi, I. P., & Sunter, A. B. (1969). "A theory for record linkage." Journal of the American Statistical Association, 64(328), 1183-1210.

  2. Harron, K., Dibben, C., & Boyd, J. (2017). "Record linkage: making maximum use of the data resource." International Journal of Population Data Science, 1(1).

  3. Christen, P. (2012). "Data matching: concepts and techniques for record linkage, entity resolution, and duplicate detection." Springer Science & Business Media.

  4. Winkler W.E., Schroeder M.A. (2006) "Matching and Record Linkage." In: Kotz S., Johnson N.L. (eds) Encyclopedia of Statistical Sciences. Wiley.

  5. Belin T.R., Rubin D.B., Schenker N., Kumar R.N.(2009) "Multiple frame sampling strategies for record linkage with proportional allocation and automatic donor imputation." Biometrics 65(3):771-779.

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