Every data team eventually inherits a system nobody understands.
· Thousands of tables
· Missing foreign keys
· Inconsistent naming
· No documentation
· Original engineers long gone
Then the business says:
“We need to migrate this.”
“We need to integrate it.”
“We need to audit it.”
Before any of that, you need something more basic:
What is the actual data model?
In most legacy systems, that model only exists implicitly inside the data.
Why Manual Reverse Engineering Fails
Typical approach:
· Browse schemas
· Inspect random rows
· Search for matching column names
Run experimental JOINs
This might work for 50 tables.
It collapses at 5,000.
Lineage tools don’t help much either — they show pipelines, not structural relationships inside the database itself.
What you really need is automated structural discovery.
How Arisyn Reconstructs Unknown Models
Arisyn approaches reverse engineering as a statistical problem.
1️⃣ Bulk Field Fingerprinting
It scans tables and extracts structural signals from every column:
· Distinct value counts
· Null distribution patterns
· Domain characteristics
2️⃣ Relationship Clustering
Columns are compared using statistical compatibility modeling — not naming conventions.
Structurally aligned fields are grouped into relationship clusters, even across systems.
3️⃣ Graph Construction
Verified relationships are assembled into a machine-readable graph:
· Tables → nodes
· Validated links → edges
· Multi-hop paths inferred automatically
This reconstructs the hidden architecture of the system.
From Discovery to Migration
Once the relationship graph exists, teams can:
· Identify core entity hubs
· Detect implicit foreign-key structures
· Generate migration mappings
· Produce structured documentation outputs
Instead of guessing how the system works, you operate from a verified structural blueprint.
Why This Matters
Legacy systems aren’t disappearing.
Cloud migrations, consolidations, and compliance audits all require deep structural understanding.
Manual reverse engineering doesn’t scale.
Arisyn turns it into an algorithmic process.
And when you’re dealing with thousands of tables, that difference is everything.
Learn more: https://www.arisyn.com

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