Legacy Mainframe Data Extraction & Integration to SQL Server

This video walks through how Centerprise AI consolidates a legacy mainframe extract, one with no SQL interface, into a live, scheduled relational database on SQL Server, entirely from one conversation. Starting from a raw Model 204 batch report (a tax agency's fixed-width taxpayer account transcript) and a separate transaction-code reference spreadsheet, Centerprise AI: - Reads the fixed-column mainframe extract and builds a reusable structured extraction template, identifying taxpayers, tax periods, and individual transaction lines automatically - Designs the relational data model (Taxpayer, Tax Period, and Transaction tables) and wires the reference spreadsheet in as a lookup that enriches transaction records at runtime, rather than becoming a separate destination table - Implements the model on SQL Server and builds the loading pipelines to populate each table in the right order - Gets scheduled to run automatically, so every new mainframe extract is loaded and enriched against whatever the reference file currently says, with no manual rebuild The model and pipeline are designed once. After that, the same pipeline keeps the database up to date on its own, every time the mainframe produces a new report. LEARN MORE Centerprise AI: https://www.astera.com/products/centerprise-ai Legacy Data Warehouse Modernization: https://www.astera.com/type/blog/legacy-data-warehouse-modernization-the-key-to-future-proof-bi Report Source documentation: https://documentation.astera.com/astera-data-stack-v9/dataflows/sources/report-source File Lookup documentation: https://documentation.astera.com/dataflows/transformations/file-lookup-transformation #DataModernization #MainframeIntegration #CenterpriseAI #LegacySystems