List matching software
What is list matching?
List matching is the process of combining lists residing at disparate sources, identifying rows that represent the same individual, and merging those rows to attain a complete and concise list where each row represents a real-word object.
List matching is commonly used in getting a holistic view of contacts and other entities by consolidating their information spread across multiple vendor, client, and partner datapoints received at regular intervals. By establishing unique IDs and match definitions to identify mis-keyed, abbreviated, and phonetic matches within and across multiple lists, companies can determine golden records and remove conflicting and duplicate entries.
How does list matching work?
Clean and standardize lists
Perform data cleansing activities to remove statistical and structural anomalies from rows of lists, such as removing leading and trailing spaces, replacing null values, fixing punctuation errors, and more.
Merge and deduplicate list rows
Merge data from duplicate rows with the help of deduplication and survivorship rules, so that maximum information is retained and combined into one golden list which represents complete view of all individuals.
Let Data Ladder handle your list matching
See DataMatch Enterprise at work
DataMatch Enterprise is a highly visual and intuitive list matching software application, specifically designed to solve customer and contact data quality issues. This is achieved by automating the list matching process and relieving you of the manual effort required to match lists containing more than a million rows. DME intelligently identifies acronyms, name reversals and variations, phonetic words, misspellings, as well as abbreviations.
DataMatch leverages multiple industry-standard and proprietary algorithms to detect phonetic, fuzzy, miskeyed, and abbreviated variations in your lists and databases. The suite allows you to build scalable configurations for data standardization, deduplication, record linkage, and enrichment across lists from multiple sources, such as Excel, text files, SQL, Oracle, ODBC, etc.