Let’s begin by answering a simple question – what is record linkage?
The definition of record linkage is the capacity to find duplicate entries in large data sets. For example, duplicate entries could represent people in one or more customer databases. Also, it could represent items in your stock systems. It enables you to find them and take actions. For example, you can merge two identical records into one. Also important, it can help you identify the entries that actually are not duplicates.
How Does Record Linkage Work?
Now we’ve explained the meaning of record linkage let’s explore how it works.
To put it simply, record linkage relies on finding unique identifiers. A unique identifier is a property that, most likely, is not going to change in the future. However, it is not so simple. Why? Because, in reality, things do change over time. So, the most important aspect is to identify the properties that can’t change. For people, it could be the date of birth, height, and gender. For objects, it could be shape or size.
There are two main methods of record linkage:
- deterministic: it is determined by the number of matching identifiers
- probabilistic: it is determined by the probability that a certain number of identifiers match
Benefits of Record Linkage
The most important benefit that record linkage brings is that it helps companies build a single customer view. Without a record linkage system, you will find information about customers spread across different data sets and even multiple systems. Obviously, this makes it impossible to get useful insight and also makes it impossible for companies to make sound business decisions.
Record linkage provides the means for your company to always extract actionable data from databases and lists. With this data, you will be able to easily build a complete customer view. With a complete customer view, companies can significantly improve their marketing efforts, make more accurate business decisions, and increase overall customer loyalty.
Also, it is worth mentioning that record linkage plays an important role in the context of the new GDPR regulation. For example, one of the most important requirements introduced by GDPR is that companies need to ask for explicit permission in order use their customer’s e-mail addresses for marketing campaigns. However, businesses use more than one channel to interact with their customers. As a result, it is practically impossible to ask for explicit permission when customer data is spread across various records or even systems.
WinPure Clean & Match is the best tool for cleansing, record linkage, and correcting data. Companies can use our award-winning software on all kinds of data such as spreadsheets, mailing lists, databases, CRMs, and many others. WinPure Clean & Match data matching and record linkage engine rely on an in-memory architecture which makes it significantly faster than most of its competitors. Also, we designed our software to scale across multiple CPUs and to process high volumes of data with utmost efficiency.
WinPure Clean & Match is able to detect and link records within and between data sets with multiple customizable fuzzy matching and phonetic matching techniques which makes it the best choice in a multitude of scenarios.
Download WinPure Clean & Match 30 DAY FREE TRIAL and find out why large enterprises such as Vodafone, Bank of America, Hewlett-Packard, McAfee, and Emirates are using our award-winning software.Learn About WinPure Record Linkage Tool