
Data Ladder
5.5#13 in identity resolution softwareAPISelf-hostedWindows
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| Fact | Data Ladder | Zingg |
|---|---|---|
| Headquarters | Suffield, Connecticut, United States | Lewes, Delaware, United States |
| Integrations | Supported import sources include text, CSV, and Excel files, SQL Server, Oracle, Teradata, Salesforce, APIs, and ODBC connections. | Documented connectors include Databricks, Snowflake, Cassandra, S3, Azure, Elastic, Exasol, relational databases and Spark-supported sources. |
| Intended users | The product page describes its visual interface as suitable for business users, IT specialists, data analysts, data scientists, and novice users. | The maker describes Zingg as a tool for analytics engineers and data scientists to integrate data silos and build unified views at scale. |
| Matching | It uses phonetic, numeric, domain-specific, and fuzzy matching algorithms when datasets lack unique identifiers. | It combines machine learning matching with rule based deterministic matching, which can use identifiers such as email, SSN, and passport ID. |
| Purpose | DataMatch Enterprise is a code-free toolkit for profiling, cleansing, matching, and deduplicating data from disparate sources. | Zingg is open source, warehouse native master data management software for resolving entities and building unified views from siloed data. |
| Support | Data Ladder offers professional and implementation services as well as team or one-to-one product training. | The comparison page lists open source support for Community and enterprise grade support for both Enterprise editions. |
It suits business users, IT specialists, analysts, and data scientists who need to clean or match data from multiple sources. It may also suit teams seeking API access or address verification options.
You want what its maker publishes above — check its page for the details.