The infor lawson etl connector that ships pre-built support for every Lawson productline (Financials, SCM, HR, Payroll), every backend (DB2 / SQL Server / Oracle), every IPA flow and every Mongoose custom table. Parallel jobs, read-only DB access, KMS-signed manifests. Source-of-truth extraction for migration, archival and analytics.
Lawson productlines run to thousands of tables across three possible database backends, with healthcare and higher-ed extensions, IPA flow metadata, Smart Notification subscriptions and Mongoose-resident shadow systems. The infor lawson etl connector ships pre-built coverage that saves months of bespoke development.
Most Lawson customers run between 3,500 and 8,000 active tables across the productline schemas, with non-obvious foreign-key relationships, multi-process-level joining rules, undocumented audit columns, healthcare-specific extension tables (340B drug attribution, GHX integration metadata, charge-master sync), higher-ed-specific extension tables (grants attribution, F&A indirect cost recovery rate history, sponsored research compliance), Mongoose-built shadow systems sprinkled throughout, and IPA flow metadata buried in the repository with embedded JavaScript that affects business logic.
Custom JDBC clients always start with a GLMASTER query and finish with a 4,000-line tangled mess that nobody on the team can debug. Different developers write different SQL for the same table family. Joins forget multi-process-level context. HIPAA covered data leaks into log files. The connector becomes the project's biggest hidden technical debt.
Syntra ETL's infor lawson etl connector replaces that with pre-built support for every productline. The connector is the product, not the script. Same engine handles full historical extract for one-time migration, delta extract on a schedule for parallel-run and ongoing analytics, and event-driven extract triggered by IPA publish-events for near-real-time downstream integration. Every mode produces hash-signed manifests and SOC 2-grade audit trail.
No more bespoke SQL hunting through Infor KB articles. Just configure scope, run, reconcile.
GL master and period balances (GLMASTER, GLAMOUNTS), AP invoices and payments (APINVOICE, APPYMTMSTR), AR customers and transactions (ARCUST, ARTRANS), fixed assets, cash management — multi-process-level aware.
Purchase orders (PURCHORDER + POLINE), item master (ITEM), inventory master (INVMASTER), inventory detail (INVENTORYDTL), buyer master (BUYER). 340B drug attribution preserved. GHX integration metadata captured.
Person master (HRPER) with extensions, department (HRDEPT), job code (HRJOB), position (HRPOSITION). Healthcare licensure / continuing education / float-pool affiliation extensions preserved.
Payroll employee (PAEMPLOYEE), deduction master (EMDEDMASTR), payroll transactions (PAYTRANSACTION). Effective-dated history for ELC / COBRA compliance preserved. Garnishment chain intact.
Full IPA flow inventory with flow XML parsing for embedded business logic. Smart Notification subscriptions catalogued. Used for IPA-to-OIC re-platforming and Smart Notification → Fusion Workflow mapping.
Mongoose-built shadow systems discovered automatically. Custom tables, custom screens, custom workflows inventoried. Used for VBCS replacement scoping or for retention in hybrid scenarios.
Six stages from kickoff to production-grade scheduled extraction.
Define in-scope productlines, IPA flows, Mongoose tables and historical window. Provision read-only DB user (DB2 / SQL Server / Oracle) with SELECT grants on scoped tables. KMS-encrypted credential storage configured.
Connector crawls Lawson backend schema, identifies active tables in scope, profiles row counts and update-frequency, maps multi-process-level partitioning, discovers Mongoose custom tables. Output: extract topology with size estimate and parallelism plan.
Single-process-level single-FY test extract validates schema, join patterns, healthcare/higher-ed extension handling, audit-column behaviour, Mongoose table discovery. Output: validated test dataset with hash-signed manifest.
Full historical extract for all process levels, fiscal years and in-scope productlines. Run in parallel with 8–16 concurrent workers, throttled to Lawson backend response-time SLAs. Output: complete Parquet dataset with per-partition manifests.
Modified-since watermarks configured per table, IPA event subscriptions established, scheduled jobs deployed. Output: production delta-extract schedule running on cron.
Monitoring dashboards configured (extract success rate, row counts vs trend, DB load impact), runbooks documented, on-call rotation established. Handover to operations team.
Built for HIPAA + SOC 2 + FERPA + SOX regulated environments.
Read-only Lawson DB user with SELECT-only grants on scoped tables. No schema mods, no triggers, no admin shortcuts. Lawson security class respected.
Every extract produces manifest signed with private key in cloud KMS. Tamper-evident — auditors can verify what was extracted, when, by whom and that nothing was modified.
Every query against PHI-containing tables (HRPER, dependents, EMDEDMASTR) logged with timestamp, user identity and purpose. Meets HIPAA Access Audit Log requirements.
DB load monitored continuously — parallelism throttled if Lawson backend response times degrade. Avoids impacting live operational performance during extraction windows.
Every extract fully replayable from manifest. Failed jobs resume from last checkpoint. Idempotent — re-running an extract produces identical output.
For strict change-window environments, extracts run against isolated DB read replica or snapshot clone. Zero touch on live Lawson backend during extraction windows.
The infor lawson etl connector is a pre-built software component that authenticates against an Infor Lawson S3 environment, extracts data from the underlying database (DB2, SQL Server or Oracle depending on tenant), reads from the LSF (Lawson System Foundation) configuration, pulls IPA flow metadata and Smart Notification subscriptions, and streams output to a destination of your choice (Fusion-ready FBDI/HDL, Parquet for analytics, JSON Lines for downstream ETL). It ships pre-built extractors for every Lawson productline: Financials (GLMASTER, APINVOICE, ARCUST), Supply Chain Management (PURCHORDER, ITEM, INVMASTER), Human Resources (HRPER, HRDEPT, HRJOB), Payroll (PAEMPLOYEE, EMDEDMASTR). Replaces the bespoke JDBC scaffolding that consultant-led Lawson migrations typically spend three months building.
Custom Lawson extraction always starts cheap and ends expensive. Lawson productlines run to thousands of tables with non-obvious relationships, multi-process-level joining rules, healthcare-specific extensions (340B, GHX integration, contract pricing), higher-ed-specific extensions (grants attribution, F&A indirect cost recovery), Mongoose-built shadow systems sprinkled throughout, and IPA flow metadata buried in the repository. A custom script that works for GLMASTER falls over on HRPER effective-dated history, then breaks again on PURCHORDER with GHX context, then breaks again on Mongoose tables. The infor lawson etl connector ships pre-built support for every productline backed by an SLA. The migration team focuses on business decisions, not on schema spelunking.
All of them in production use. Financials: GLMASTER (GL master), GLAMOUNTS (period balances), APINVOICE (AP invoices), APPYMTMSTR (payment master), ARCUST (customer master), ARTRANS (AR transactions). Supply Chain: PURCHORDER (PO header), POLINE (PO lines), ITEM (item master), INVMASTER (inventory master), INVENTORYDTL (location detail), BUYER (buyer master). HR: HRPER (person master), HRDEPT (department), HRJOB (job code), HRPOSITION (position). Payroll: PAEMPLOYEE (payroll employee), EMDEDMASTR (deduction master), PAYTRANSACTION (payroll transactions). IPA flows: full repository inventory with flow XML parsing for embedded business logic. Smart Notifications: every subscription. LBI / Birst content registry. Mongoose custom tables: full catalog discovery.
Lawson runs on three database backends in production: IBM DB2 (the classic Lawson backend, still common in long-tenured hospital deployments), Microsoft SQL Server (the most common backend in newer Lawson installs, especially Lawson 10), and Oracle Database (some healthcare and higher-ed deployments). The connector ships native JDBC drivers and extractors for all three. Authentication uses backend-native mechanisms (Kerberos for DB2, SQL Server authentication or AD, Oracle wallet). Query optimisation respects backend-specific quirks (DB2 partitioning, SQL Server columnstore, Oracle materialised views). Customers with DB2-on-AS/400 or LinuxONE deployments get the same throughput as customers on SQL Server commodity hardware.
The connector authenticates with a read-only Lawson DB user provisioned with SELECT-only grants on the tables in scope — no schema modifications, no triggers, no admin shortcuts. Lawson security classes are respected: the read-only user is mapped to a Lawson actor with read-only data area access, ensuring that the extraction stays within the same security perimeter the organisation already audits. Connection credentials stored in cloud KMS, every query logged with timestamp, user identity and row count for SOC 2 audit, read-only user can be revoked instantly. For organisations with strict change-windows (mid-month-close periods, payroll cycle peaks), extractions can run against an isolated DB read replica or snapshot clone — zero touch on live Lawson.
Yes. The connector supports cron-style scheduling, event-driven triggers (DB CDC watermarks, IPA event subscriptions) and one-shot manual runs. Common scheduling patterns: nightly full extracts during assessment phase, hourly delta extracts during cutover parallel-run, weekly archive-window extracts after go-live for any long-tail historical capture, period-end-of-month full extracts for finance close validation. The scheduler handles dependency graphs (extract item master before lot detail, extract customer master before AR transactions, extract HRPER before EMDEDMASTR) and respects rate limits and DB load windows automatically. Failed jobs retried with exponential back-off, full audit trail captured for compliance review.
Every extract run produces a manifest: list of tables/IPA flows/configurations hit, row counts per table per fiscal year per process level, byte counts, content-hash per file, start/end timestamps, read-only user identity. The manifest is signed with a private key held in cloud KMS, producing a tamper-evident record. When the data lands in Fusion or in long-term archive, the reconciliation process re-verifies the manifest signature — meaning auditors can confirm what was extracted, when, by whom and that nothing was modified post-extract. For Lawson estates with HIPAA covered data (HRPER, dependents, EMDEDMASTR benefits), the signed manifest is the HIPAA Access Log evidence. Big 4 firms accept this evidence pattern for SOX, HIPAA, CMS and FFATA audit.
Yes — and many customers do. After migration cuts over to Fusion, the same infor lawson etl connector continues to pull from the read-only Lawson archive (kept as historical source-of-truth) or from the Syntra cloud archive (where Lawson has been fully decommissioned), feeding the downstream analytics stack: Snowflake, BigQuery, Databricks, or back into OTBI for unified historical-plus-current reporting. The same Parquet output, the same hash-signed manifests, the same audit trail — used now for finance analytics, supply-chain dashboards, payroll reconciliation, HIPAA covered-data queries and FFATA grant reporting. Hospital quality teams use it to query Lawson historical lot/serial for recall investigations. Higher-ed grants teams use it for sponsored research compliance reporting. One connector, many use cases.
Book a 30-minute walkthrough. We'll connect to a sample Lawson environment, run a multi-process-level extract live, and show you the manifest, the reconciliation output and the audit trail.