Identity Resolution in Customer Data with Table Indexer

<p>This use case demonstrates how <strong>M|Box's Table Indexing Nodes</strong> can be combined to perform <strong>efficient, fast and fault-tolerant Customer Identity Resolution </strong>across multiple data fields.</p><p>Workflow Overview:</p><ol><li><p>The workflow loads:</p><ul><li><p>A master data table containing 100,000 customer records (IDs, names, addresses etc.)</p></li><li><p>A search table with an incoming customer record that needs to be verified against the master data.</p></li></ul></li><li><p>The <strong>Character Mapper</strong> creates an invisible mapping that expands umlauts (e.g. ö → oe). The <strong>Table Indexer</strong> then builds a multi-field index over relevant attributes such as customer names, birthdates, and telephone numbers.</p></li><li><p>The incoming customer record is matched against the index using the <strong>Table Index Matcher</strong>, which performs a weighted, multi-field search. Fields that are not part of the search criteria are passed through the indexing nodes, ensuring that the result contains the complete matched customer record.</p></li></ol><p>Index-based matching with the <strong>M|Box Table Indexing Nodes</strong> enables fast and scalable identity resolution across multiple customer attributes. By combining multi-field indexing with weighted search, customer records can be reliably matched even when individual fields contain variations or incomplete information.</p>