Finding and removing duplicates through software tools
Tags: data, deduplication, dataquality, mergepurge
Published: 2022-07-07 11:53:46

In Datafold’s recent survey on [The State of Data Quality in 2021](https://www.datafold.com/blog/the-state-of-data-quality-in-2021), most respondents said that they do not use any tool or software to clean data, and manually perform data quality verification and fixes. Nowadays, process optimization and operational efficiency are impossible without technology. A team that relies on manual effort to execute complicated tasks, such as bulk data cleansing and deduplication, is bound to make mistakes and produce inconsistent results.  
 
In this blog, we will look at what a [data deduplication software](https://dataladder.com/data-deduplication-software/) is, the most crucial features and functionalities found in such a tool, and how it can help your data quality teams to save time and money. Let's get started. 
 

## Data deduplication software 

Data deduplication software is a tool that efficiently executes the data deduplication process which includes: 
Comparing two or more records, 
Computing the probability of these records being similar or belonging to the same entity, 
Deciding which information to retain and which to override, 
Merging records to get a single comprehensive record for an entity, 
Deleting and discarding duplicate records. 
 
The data deduplication process requires advanced knowledge about data and how to deal with it to get optimal results. Otherwise, you may end up losing crucial information. Data deduplication tools come with advanced data profiling, cleaning, and matching algorithms – that are capable of processing millions of records in a matter of minutes. This is where automated tools can perform better and more quickly, accurately, and consistently – as compared to human effort.  
 

## Prerequisites of accurate data deduplication 

Since datasets contain a variety of data quality errors, the accuracy of your data deduplication process depends on a number of pre-requirements, such as: 
Data residing at disparate sources must be combined or integrated together for the process. 
All records must follow a standardized format and pattern. 
Data values must be present in the same data type and unit of measurement. 
Data match definitions must be configured to define which attributes should be used for matching data. 
Rules must be defined to compare duplicate records and make decisions to merge and override data. 
There must be a way to export or store duplicate records in case you don’t want to delete them. 
 

## Features of data deduplication software 

If you take the prerequisites into consideration, it becomes clear that a data deduplication tool must be equipped with all these features. Let’s discuss the most crucial features to look for in data deduplication software: 
**Data ingestion:** the ability to import, connect, or integrate data residing across disparate sources, including local files, databases, third-party applications, etc. 
**Data profiling:** the ability to uncover hidden details about your data in terms of blank values, incorrect patterns, formats, and datatypes, to identify possible cleaning opportunities. 
**Data cleansing and standardization:** the ability to eliminate incorrect information and transform data values to follow a standardized view across all sources. 
**Data parsing and merging:** the ability to divide one column into multiple columns, or inversely, combining two or more columns into one. 
**Data match configuration:** the ability to configure match definitions and tune algorithms according to the nature of data to get optimal results. 
**Data deduplication:** the ability to execute different types of matching (exact or fuzzy) and compute the probability score of two or more records belonging to the same entity. 
**Data merge and survivorship:** the ability to merge and override duplicate records and get a single comprehensive view of entities. 
Data export or load: the ability to transfer a single source of truth to the required destination, such as a local file, database, or any third-party application. 
 

## Factors to consider while employing data deduplication software 

There are quite a few vendors in the market that offer the features mentioned above in their data deduplication tools. But there are some factors to consider while choosing such a tool: 
What does your organization require? 
Data quality means something different for every organization. For this reason, instead of buying a tool that you heard works for somewhere else, you need to find out what will possibly work for you. Here, a list of data quality KPIs will help you understand what you are looking to achieve and whether the solution under consideration can help you implement that vision. 
How much time and budget are you willing to invest in this tool? 
Adapting to technological changes in an organization asks for time and money. You may need to assess what budget you are willing to invest in this tool. Also consider the fact that it might take some time for your team members to learn the new tool and use it efficiently. 
What does your data quality team prefer? 
This is a key player in your decision to choose a data deduplication tool. [Data quality team](https://dataladder.com/building-a-data-quality-team-roles-and-responsibilities-to-consider/) members are often present in organizations as data analysts, data stewards, or data managers. These individuals spend most of their day dealing with multiple data applications, sources, and tools. Let them decide which tool helps them get their job done most efficiently.  
 

## Conclusion 

Data deduplication is the first step in enabling a reliable data culture at a company and creating a single source of truth that is accessible to everyone. When your datasets are free from duplicates, you can get many benefits, such as accurate data analysis, customer personalization, data compliance, brand loyalty, and operational efficiency. Investing in such tools will definitely reduce rework and free up your team members to focus on more important tasks.