Merge Purge Software
Combine data from databases, files, or applications, decide which records should stay or go, and create survivorship rules easily with the highest-rated merge purge software in the market.
|Features of the solution||Data Ladder||IBM Quality Stage||SAS Dataflux||In-House Solutions|
|Match Accuracy |
(Between 40K to 8M record samples)
|Software Speed||Very Fast||Fast||Fast||Slow|
|Purchasing / Licensing Costing||80 to 95% Below Competition||$370K+||$220K+||$250K+|
|Time to First Result||15 Minutes||2 Months+||2 Months+||3 Months+|
|Comments||Above tests were completed on 15 different product comparisons with university, government, and private companies (80K to 8M records). This includes the effect of false positives.||Need multi-threaded. in memory, no-SQL processing to optimize for speed and accuracy. Speed is important, the more match iterations you can run, the more accurate your results will be.||Includes base license costs. 2014 prices or later, in-house, includes salary + benefits. Note in-house implementations had a 10% chance of losing in-house personnel, so over 5 years half of the in-house implementations had lost the core member who ran and understood the matching program.||A metric for ease of use. This is the time to ﬁrst result, not necessarily full cleansing.|
|Match Accuracy (Between 40K to 8M record samples)||Data Ladder: 96%IBM Quality Stage: 91%SAS Dataflux: 84% In-House Solutions: 65-85%*|
|Software Speed||Data Ladder: Very FastIBM Quality Stage: FastSAS Dataflux: Fast In-House Solutions: Slow|
|Purchasing / Licensing Costing||Data Ladder: 80 to 95% Below Competition IBM Quality Stage: $370K+ SAS Dataflux: $220K+ In-House Solutions: $250K+|
|Time to First Result||Data Ladder: 15 Minutes IBM Quality Stage: 2 Months+ SAS Dataflux: 2 Months+ In-House Solutions: 3 Months+|
Studies reveal that 69% of businesses struggle with data quality issues when attempting to eliminate data silos across the enterprise. The average enterprise uses 65 applications, any of which could contain records pointing to the same entity. As a result, duplicates appear when data is being consolidated, requiring manual deduplication which costs time and resources.
Variations in names, phone numbers, and addresses make it difficult to deduplicate.
Spelling errors and lack of standardization in input data.
Data that includes contact information often comes from multiple files that are in different software formats.
Third-party data may exist in different formats and specifications.
Incorrect source-to-target mapping creates duplicates when data is combined .
Merge purge is the process of combining two or more lists or files, identifying and/or combining duplicates, and eliminating (purging) unwanted records. Through phonetic and fuzzy matching algorithms, human errors such as typos are located and removed from data. The task of merge-purging a database can be expensive and time-consuming, but with data quality tools like merge purge software, cleaning up dirty data is easier, faster, and more accurate than ever before. The right merge purge software should be easy to use by anyone and in any situation. You don’t need to be a data scientist, data analyst, IT professional or be in the Big Data industry to benefit from clean data.
Find information spread across data sets that belong to the same entity and create a single record with complete information.
Identify duplicates and linked records using sophisticated fuzzy matching algorithms. Choose whether to merge and purge records, or survive specific data.
Define data survivorship rules to merge linked records into a “golden” record and prevent data loss by extracting additional data to separate fields.
Cleanse and standardize data prior to matching (street to street, eliminating unnecessary syntax in phone numbers, etc.)
Rated faster and more accurate than IBM and SAS, our merge purge software consistently had the least number of false positives in independent studies.
Apply over 300,000 built-in rules for names (Jon, Jonathan, John), phone numbers, address, and company name for standardization.
Identify matches accurately with percent matches between records and setting minimum percent match thresholds by field.
Find and replace unwanted characters, patterns, and specific words from millions of records to automate list standardization and cleaning with merge purge tools.
All businesses have multiple sources of data. Customer data is present in forms filled by customers, databases created by employees, and data captured from marketing and sales activities. Product data is provided by multiple vendors in multiple forms. This data can provide useful insights and help the business increase operational efficiency but there is one problem in using it. Since the data came from different sources and in different formats, how do you merge relevant data to create master records?
Situations like these call for merge purge software. Merge purge processes can combine data from different sources intelligently and establish accurate matches. This is accomplished by Data Ladder’s use of multiple data cleansing and matching technologies. A combination of established, industry-best fuzzy matching, phonetic, and domain-specific algorithms like Jaro-Winkler Distance, Probabilistic Jaccard, Metaphone 3, and Name Variant, along with our proprietary fuzzy identification logic, is used to find duplicate data points. Matching is further improved with over 300,000 built-in data standardization rules and pattern matching techniques to correct names, addresses, phone numbers, email addresses, and more.
Merge purge software gives your business the ability to use its data to its fullest potential. Data can be analyzed to find insights, increase efficiency, and discover problems, ideally, if you have a “single source of truth” that supports integration with enterprise-wide applications and systems. Merge purge allows you to choose how the data should be merged and purged. Pick the data survivorship rules that serve your purpose best and our merge purge tool will go through millions of records, combining them into complete golden records. Your original data is preserved in its original form, and a new dataset is created containing all the information.
Our merge purge solution can process lists with 100 million+ records and has been rated the fastest and most accurate list cleaning software in multiple independent studies, consistently outperforming competing solutions from IBM and SAS. Whether you’re a business user or IT, experience the power of code-free, intuitive data cleansing and increase operational efficiency today.
During your 30-day trial, you can access DataMatch Enterprise™ risk-free. The software is user-friendly and easy to install – what you see is what you get! However, we recommend a 30 to 60-minute non-obligatory online consultation with one of our subject matter experts to help you get the most out of your free trial.