One workflow to turn raw enterprise data into a trusted product
Pinnova gives data teams a shared, six-step discipline — from first inventory to internal adoption — so data stops being a liability and starts being something the business rallies around. Proven on Supply Chain and Finance, it works for any data domain, and installs entirely inside your firewall, free to start.
Register data products with real, named ownership
Every data product maps to one governed data entity and a named owner on both sides of the business — so nobody has to guess who to call when something breaks.
- Technical and business owners, both responsible and accountable, on every product
- Each product maps to one governed data entity and its source system
- Plain-language description kept alongside the technical definition
- Owners resolve to a named data steward directory, with email and phone on file for every technical and business owner
- Business users self-request access to a functional group's products; the group's leader or business owner approves it — no ticket queue
Know every dataset you actually have
Every data entity — a table, a view, a HANA calculation view — is registered once with its connection, schema, and object name, then connectivity-tested before anything downstream runs against it.
- Entities mapped to connection, schema, and object across every source system
- One-click connectivity tests before profiling or validation runs
- Connects to SAP HANA, Microsoft SQL Server, MySQL, PostgreSQL, Oracle, Snowflake, Databricks, and DB2
Understand the shape of your data before you build on it
Every run captures row counts and full schema metadata — column name, data type, length, and scale — plus downloadable data samples, so teams stop discovering data problems in production. A schema comparison report lines every data product up against every other, surfacing column overlap, gaps, and datatype mismatches automatically.
- Row-count volume tracked and charted by data product, run over run
- Full column schema — name, type, length, scale — refreshed automatically
- Downloadable data samples for every profiled entity
- Pairwise schema comparison across products, with auto-generated improvement suggestions
- Mark a data product Sensitive to keep row counts and schema while skipping sample data extraction entirely
Reconcile source and reference data down to the row
Every validation checksums your source entity against a reference entity — grouped by block and subblock, filtered to the records that matter, and compared within a defined tolerance. When it doesn't match, Pinnova drills down to the exact rows.
- Checksum reconciliation with configurable block, subblock, and tolerance
- Automatic drill-down to mismatched rows, exported as CSV
- Pass rate and quality score tracked per data product, run over run
Track how the pipeline is performing — and know the moment it isn't
Every validation run reports its own runtime, and Pinnova tracks average and peak execution time per data product over time, so slow-downs show up before they become an incident. When a run fails, Pinnova emails the responsible owner automatically — and if the same check keeps failing, escalates to the accountable owner too.
- Average and peak runtime tracked per data product
- Trend charts across every historical run
- Automatic email alerts to the responsible owner on every validation failure, escalating to the accountable owner after repeated failures
- Every notification attempt — sent or failed — is written to an audit trail for compliance review
Point every data product at where people can actually see it
A trusted data product no one knows about doesn't change decisions. Each data product registers against one or more dashboards — Power BI today — and every dashboard carries a named responsible and accountable owner, so employees always know where to look and who to ask.
- Data products map many-to-many to registered dashboards, so one report can serve several products
- Every dashboard carries a named responsible and accountable owner, not just a link
- Employees get a personal "My Data Products" view, scoped to the functional groups they're approved for — Roadmap: full-text search as the catalog grows
- Optional Microsoft Entra ID single sign-on for employees, alongside local accounts and an optional single-email-domain restriction
Sixteen ready-made procure-to-pay analyses, run against your own data
Pinnova BDS ships curated SQL "skill" packs for the questions procurement, finance, and audit teams keep asking. Point one at a configured connection — the Reference Data Models on SAP HANA, or your own views — and export the answer as CSV.
- Three-way-match exceptions, duplicate invoice detection, and P2P controls & fraud signals
- Maverick spend, price variance, supplier spend concentration, and category spend planning
- Contract utilization & expiry, payment terms & discount optimization, inventory & working capital
- Material and vendor master data quality checks, GR/IR aging and close, and AP processing efficiency
See the platform on your own data
Download the free tier and run it against your own SAP HANA, SQL Server, or other connected data sources today.