DataMatch Enterprise

DataMatch Enterprise is Data Ladder's data matching software for deduplicating and cleansing records across files and databases without code. Quote only.

DataMatch Enterprise finds the records in a company's data that describe the same person, business or address, then flags or merges them. Data Ladder, a data quality software company in Suffield, Connecticut, makes it alongside Product Match, a separate tool for product data. The job it takes over is the slow comparison of spreadsheets and database exports, where spelling variants, nicknames and stray formatting hide duplicates. It runs as a desktop toolkit, and a Server Edition also ships as a Docker build. A project usually opens with data profiling, which reports blank values, distinct counts, frequencies and patterns for every field. The data cleansing and standardization tools then fix casing, trim spaces, remove characters, fill nulls and clean telephone numbers, with the Pattern Builder for custom formats. Built-in libraries handle name verification and common nicknames. Match configuration compares records with exact, fuzzy and intelligent matching, and Match Scoring sets the threshold at which a pair counts as a duplicate. Address Verification checks US addresses against USPS CASS, DPV, LACSLink and SuiteLink data. The toolkit suits data analysts, CRM administrators and operations staff who own a customer, member or patient list that has grown untidy. Its no-code screens let business users build profiling, cleansing and matching rules without a developer. Healthcare, education, government, retail, finance and insurance teams are the sectors Data Ladder builds for, along with sales and marketing. Buyers choose between three editions: the base toolkit, one adding the API for real-time fuzzy search, and one adding Address Verification. Organizations that must keep records inside their own network can run it on their own machines, on Linux or in their own cloud. Typical jobs are clearing duplicates from a contact list before a mailing and linking one customer's records across several systems. Records come in from Excel workbooks, CSV and text files, XML and JSON, Oracle and other SQL databases, and Snowflake through its data connector. Results arrive as a table of matched pairs with a score for each, ready for a reviewer to check. Recurring work runs from the command line or the Scheduler, while the REST API lets another application send records for matching. DataMatch Enterprise fits the team that must settle which records are the same before anyone can rely on the data.