A merge purge is a pivotal function for business operations such as direct mail marketing and obtaining a single source of truth. However, many organizations still believe that the merge purge process is solely limited to Excel techniques and functions that do very little to rectify increasingly complex needs of data quality.
This guide will help business and IT users understand the merge purge process, and possibly make them realize why their teams can no longer continue merging and purging through Excel.
Let’s begin!
What is a Merge Purge Process or Function?
Merge purge is the process of bringing several sources of data into one place while at the same time removing bad records and duplicates from the source.
It can be simply described in the following example:
Notice that the above image has three similar records with multiple issues related to data quality. Upon applying a merge purge function to this record, it will be transformed into a clean and singular output such as the example below:
Upon merging and purging the duplicates from multiple sources of data, the result shows a consolidated version of the original record. Another column [Industry] has been appended to the record, sourced from yet another version of the record.
The output of a merge purge process creates records that contain unique information that serves the business purpose of data. In the above example, upon being optimized, the data will serve as a record that is reliable for marketers in mail campaigns.
Best Practices for Merging and Purging Data
Regardless of the industry, business, or company size, merge purge processes serve as the basis for data-drive objectives. Although the exercise was solely limited to combination and elimination, today merging and purging has evolved into an essential mechanism which enables users to analyze their data in great detail.
Despite the process being largely automated now through extensive merge purge software and tools, users still need to maintain the best practices for data merge purge. The following are some I highly recommend you to follow:
- Staying Focused on Data Quality: Before carrying out a merge purge operation, it is essential to clean and standardize data, as this ensures that the deduping process is easier. If you dedupe without having the data cleaned, the results will only disappoint you.
- Sticking to a Realistic Plan: This is in case a simple data merging process isn’t a priority for you. It’s recommended that you establish a plan which will help assess the type of records you’re looking to merge and purge.
- Optimizing Your Data Model: Generally, after an initial merge purge process, companies develop a better understanding of their data model. Once a preliminary understanding of your model is developed, you can make KPIs and reduce the time being spent on the overall process.
- Maintaining a Record of Lists: Purging a list isn’t necessarily about deleting the list entirely. Any data merge purge software will enable you to save the records and maintain a database of each change that has been made to the list.
- Keeping a Single Source of Truth: When user data is sourced from several records, discrepancies are faced due to disparate information. In this case, merging and purging helps create a single source of truth. This includes all necessary information about the customer.
The Benefits of Self-Service Merge Purge Software
An effective solution to creating a single source of truth while making sure you follow the remaining best practices, is getting a merge purge software. Such a tool will overwrite old records using new information through a data survivorship process.
Moreover, self-service merge purge tools can enable business users to conveniently merge and purge their data records without making it necessary for them to have in depth programming knowledge or experience.
The ideal merge purge tool can help business users with:
- Preparing data through assessment of errors and information consistency
- Cleaning and normalizing data in accordance with defined business rules
- Matching multiple lists via a combination of established algorithms
- Removing duplicates with a high accuracy rate
- Creating golden records and obtaining a single source of truth
- & much more
Needless to say, in an era where automation has become essential for business success, companies cannot afford to delay optimizing their business data. Thus, modern data merge/purge tools have now become the flagship solution for age old problems related to complex processes for merging and purging data.
Data Ladder
A company’s data is one of their most valuable assets – and just like any every other asset, data needs nurturing. Although companies have become laser focused on acquiring increasing amount of information and bolstering up their data collection, the acquired data ends up remaining dormant and taking up expensive CRM or storage space for long periods of time. In such cases, the data needs to be purged before it can be put to business use.
However, the complex process of merging/purging can be simplified through a one-stop merge purge software that helps you merge data sources and create records that are actually valuable.
Data Ladder is a data quality software company dedicated to helping business users get the most out of their data through data matching, profiling, deduplication, and enrichment tools. Whether it’s matching millions of records through our fuzzy matching algorithms, or transforming complex product data through semantic technology, Data Ladder’s data quality tools provide a superior level of service unmatched in the industry.
