The Importance of Entity Resolution in Data Management

Are you tired of dealing with data that's scattered across multiple sources, with varying degrees of accuracy? Do you find yourself struggling to make connections between disparate data sets, even when they seem to relate to the same individuals or entities? If so, you're not alone. This is where entity resolution comes into play.

Entity resolution is a vital component of data management, allowing you to accurately identify, consolidate, and update your records regardless of where the data is originally coming from. It is a technique for identifying and linking records that refer to the same entities. Businesses, healthcare companies, government agencies, and virtually any organization that touches data benefit from entity resolution.

At its core, entity resolution is about making sense of data. For example, consider a hypothetical bank with multiple branches in different parts of the country. Over time, customers open accounts at different branches, and the branches store customer data in different ways. Their names might be spelled differently, their identification numbers might have typos, their contact information could be mismatched or outdated, and they could even be registered under different branch codes.

Without entity resolution, the bank would be forced to treat each of those customer records as separate entities, with no easy way to tell which records refer to the same people. This creates problems when customers visit different branches, open new accounts, or try to update their information. The bank may lose valuable information and struggle to provide satisfactory customer experiences.

This is just one example of how entity resolution can be essential in data management. Let's take a closer look at what entity resolution is, why it's important, and how it can help you better manage your enterprise data.

What is Entity Resolution, and How Does it Work?

Entity resolution is a process that involves the identification, consolidation, and normalization of data to reconcile records that are likely about the same real-world entity. In essence, it is a method for disambiguating entities from within data sources such as databases, spreadsheets, or other data storage technologies.

When we talk about entities, we usually mean people, organizations, events or things that can be uniquely identified in the real world. Take the example of a person. A person may have multiple representations in different databases or data sources, and each representation may be incomplete, or the same data may appear with typos or variations. When the person's identities are resolved, the goal is to combine all the data from different sources into a single, accurate record, capturing all the relevant information from all available sources. Typically, the entity resolution process consists of the following steps:

  1. Data Preparation - Before resolving entities, the data should be cleaned, deduplicated and preprocessed to ensure that redundant or low-quality data sources are filtered out, and data quality is improved .

  2. Entity Profiling - Entity profiling is a process of extracting key attributes or features of entities from various data sources, analyzing them to obtain relevant information, and creating a data profile. Data profiling is often the first step in developing an entity resolution system.

  3. Entity Matching - This is the core of the entity resolution process—identifying matching pairs of entities from different sources. This process involves comparing entity profiles generated in the previous step.

  4. Entity Consolidation - After identifying matching pairs, the data from different sources must be merged to create a unified, accurate record that contains all the available information.

  5. Validation and Updating - Finally, the newly consolidated data set can be validated and updated before being used to support business decisions, research or analysis.

Overall, entity resolution ensures that the same entity is not represented multiple times in the same data set. By filtering out redundant or incorrect data, it also improves data quality and accuracy.

Why is Entity Resolution so Important for Data Management?

In our hyperconnected world, data is the backbone of the digital economy. Almost every organization today generates or handles large amounts of data. High-quality data is essential for making sound business decisions and providing valuable services to customers.

Entities can appear in many segment-specific domains or applications, such as CRM, marketing tools, web analytics, sales pipelines, or HR systems. More often than not, those applications operate in silos, and using them to create a comprehensive view of any one individual often results in incomplete or inaccurate data. Entity resolution helps consolidate disparate data sources to create a complete record, resulting in a holistic view of a customer or any other entity across any segment-specific domains in which that the entity appears, enabling better understanding of customers and more effective engagement.

Data is only valuable when it is accurate and complete. Entity resolution ensures that your data is both, allowing you to make informed decisions with greater confidence. By providing a single, unified view of customer data, it can help improve customer engagement, increase marketing and sales effectiveness and streamline operations.

Entity resolution can enhance the quality of your data by removing errors, improving accuracy, and minimizing duplication. Inefficient, inaccurate, or incomplete data costs organizations millions of dollars every year, from misguided marketing campaigns to incorrect billing. According to Gartner, poor data quality costs organizations an average of $15 million per year.

Entity resolution guarantees that data is connected and interoperable, allowing businesses to create big data-driven insights with greater accuracy and efficiency. With big data revealing driving revenue growth and market intelligence, entity resolution never been more important.

How Entity Resolution Can be Applied

The basic principles of entity resolution can be applied to many types of data, and the benefits can be profound. Here are a few examples of use cases across industries:


Healthcare organizations require comprehensive, accurate patient data to make informed decisions about treatment and care. With entity resolution, healthcare providers can merge patient data from different sources, such as electronic health records (EHRs), claims data, lab results, and IoT devices, creating a 360-degree patient view across different care settings for informed care coordination and clinical decision-making.

Retail and E-commerce

Retail and e-commerce organizations can use entity resolution to unify customer identities by merging offline and online data from different customer interactions. Effective entity resolution can significantly increase ROI of marketing campaigns, create more personalized customer experiences, reduce customer churn, and improve customer lifetime value.

Financial Services

Further examples can be seen in the financial services sector, where managing client data is of critical importance. By using entity resolution to reconcile customer data from multiple channels, a unified, cross-channel view of individual customers can be established. By doing so, institutions can enjoy significant advantages in customer retention and cross-selling, risk management, and anti-fraud measures

Challenges in Entity Resolution Implementation

The implementation of entity resolution techniques can provide significant benefits for data management, but it is not always easy to achieve. There are several common challenges that organizations face when implementing entity resolution:

  1. Data Quality - The quality of data is critical in the entity resolution process. Poor data quality can result in incorrect entity matching and consolidation, leading to inaccurate data and lower confidence in decisions derived from such data. Therefore, cleaning and preprocessing data are vital steps to ensure accuracy and completeness of the data.

  2. Data Volume - Entity resolution is computationally complex, and the more records that need to be matched and consolidated, the more processing power and techniques are needed. Scalability can be a challenge in implementation, and efficient methods for handling large datasets should be utilized.

  3. Data Governance - Inaccurate or incomplete data can originate from many sources. Interoperability can be a challenge when data is housed in different data silos or data models such as databases, spreadsheets, or flat files. Having an effective data governance strategy can help organizations tackle data quality, scalability and operational issues.

  4. Security and Privacy: Entity resolution involves aggregating data from different sources to create a complete record of an individual. As such, concerns around data security and privacy are prevalent. Implementing adequate measures to make sure that data is protected and shared only with authorized individuals is essential to ensure compliance with regulations such as GDPR or CCPA.


In the world of data management, entity resolution is an essential tool for creating a cohesive, accurate view of the entities that we deal with on a daily basis. Whether you're working in healthcare, finance, retail, or any other industry where data is king, you can benefit from entity resolution techniques. These techniques enable organizations to manage and process big data more effectively, improve decision making, and enhance customer engagement.

While there are many challenges to implementing entity resolution successfully, these are outweighed by the potential benefits. If your data is scattered across different sources, with inconsistencies, and duplicates, it's time to start thinking about entity resolution and how it can help you unlock the power of your data.

At, we provide the resources and support you need to get started with entity resolution. As a community dedicated to helping organizations achieve better data management practices, we offer tools, guidelines, and best practices, helping you create a more comprehensive, accurate view of your business data. Join us today, and discover the power of entity resolution for your organization.

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