Data integrity problems are quiet until they're not — a duplicate record here, an orphaned row there, and eventually reports stop making sense or an app crashes on data it didn't expect. We diagnose the actual scope of what's broken before touching anything, because with corrupted data, the wrong fix can turn a contained problem into a bigger one.
1:1 Database Support · Fixed-Price & Hourly Options · Fast Turnaround
This Is For You If...
You're a founder and something in your database doesn't add up — duplicate customers, mismatched totals, missing links
Your team noticed a foreign key pointing to a record that no longer exists
You're a student or freelancer whose database has drifted from what the schema says it should look like
A bug or bad migration left data in an inconsistent state and you're not sure how far it spread
Reports or queries are returning results that don't make sense given what should be in the database
Self-Diagnostic Checklist
Run through this before making any further changes yourself — with data integrity issues, the wrong next step can spread the damage:
Ask Yourself | What It Suggests |
Is this duplicate records, missing/broken relationships, or just wrong values? | Each of these needs a different diagnostic and fix approach |
Do you know roughly when this started, or how long it's been present? | Helps scope how far the issue may have spread and what's recoverable |
Is this affecting one table, or does it cascade across related tables? | Referential integrity issues often ripple — a broken link in one place can affect several |
Did this follow a specific event (a migration, a bad deploy, a bug in write logic)? | Points to a specific, traceable cause rather than gradual drift |
Have you already tried to manually fix any of the bad data? | Tells us what's already been changed, which matters for understanding the current state |
Do you have a recent backup? | Critical context — tells us what's recoverable if some of the affected data needs to be restored |
If you're unsure on several of these, stop before making further manual changes and reach out — assessing the actual scope first is safer than guessing.
Data Corruption & Integrity Issues We Fix
Fix Corrupted Data
Corrupted data — values that are garbled, truncated, or structurally invalid — can come from a failed write, a bad migration, or an application bug. We identify the actual scope of the corruption and the safest way to correct or restore it.
Resolve Duplicate Records
Duplicate records, where the same real-world entity (a customer, an order, a product) exists as multiple database rows, usually stem from a missing uniqueness constraint or a write process that creates new records instead of updating existing ones. We identify true duplicates, merge them carefully, and fix the underlying cause so it doesn't keep happening.
Fix Broken Foreign Key / Referential Integrity Issues
A broken foreign key, or a general referential integrity violation, means a relationship between tables no longer holds — often from a delete that didn't account for dependent records. We identify every affected relationship and restore consistency without further data loss.
Fix Orphaned Records
Orphaned records — rows in a child table with no corresponding parent record — typically result from a parent being deleted without a proper cascade rule. We identify the orphaned rows and decide, based on your actual data, whether to relink, restore the parent, or safely remove them.
Fix Inconsistent / Mismatched Data Across Tables
When data that should agree across related tables doesn't match — like a total stored in one place disagreeing with the sum of related detail rows — we trace which side is actually correct and reconcile the discrepancy.
Fix Missing Required Data / Incomplete Records
Incomplete records, where required fields are unexpectedly empty or entire records are missing data they should have, often trace back to a write process that didn't enforce required fields properly. We identify the gap and the process that allowed it.
Fix Data Type / Format Integrity Violations
Data that violates its expected format or type — text in a numeric field, malformed dates, values outside an expected range — points to missing validation at the point of entry. We correct the existing bad data and identify where validation needs to be enforced.
Fix Data Integrity Issues After a Failed or Partial Migration
When a migration partially completes or fails midway, it can leave data in an inconsistent state — some records updated, others not. We assess exactly what state the data is in and reconcile it safely.
Fix Cascading Data Corruption Across Related Tables
When a single bad write or deletion cascades into inconsistency across multiple related tables, isolating the original source is critical before fixing the downstream effects. We trace the corruption back to its origin rather than just patching each affected table independently.
Fix Unique Constraint Violations / Missing Constraints
Unique constraint violations, or data that reveals a missing uniqueness constraint that should have existed from the start, mean duplicates or conflicting values were able to enter the database. We fix the existing bad data and help you add the constraint that should have prevented it.
Fix Data Corruption from a Bug in Write Logic
When corrupted or inconsistent data traces back to a bug in the application code that writes to the database, fixing the data alone isn't enough — the underlying write logic needs to be fixed too, or the corruption will continue. We address both.
Data Integrity Audit / Cleanup
For a broader data integrity audit, or general database cleanup rather than one specific known issue, this is a proactive review across your data to catch duplicates, orphaned records, and inconsistencies before they cause a visible problem.
Don't see your exact situation listed above? Tell us what looks wrong and we'll help assess it — most data integrity issues fall into a variation of the above.
What We Need From You
What to Share | Why It Helps |
A specific example of the bad data you've noticed | Concrete examples (a specific duplicate, a specific broken relationship) speed up diagnosis significantly |
Roughly when this started or was first noticed | Helps scope how far the issue may have spread |
Whether you know of a specific triggering event (a migration, a bug, a bad deploy) | Points us toward a likely root cause rather than starting from zero |
Whether you have a recent backup | Critical for understanding what's recoverable if restoration is needed |
Read access to the affected tables/database | Lets us assess the actual scope directly rather than working from a description |
Whether the affected system is currently live/actively being written to | Changes how carefully and quickly we need to move |
Common Mistakes to Avoid
Instinct | Why It Doesn't Help | Do This Instead |
Manually deleting duplicate or "bad-looking" records without checking their relationships first | Can orphan related records elsewhere, turning one problem into several | Check what references a record before deleting it, or use a proper merge process |
Restoring an entire table from backup to fix a few bad rows | Loses any legitimate, correct data that changed since the backup was taken | Restore or fix only the specific affected records where possible |
Adding a uniqueness constraint immediately, without first resolving existing duplicates | The constraint will simply fail to apply, or block legitimate future writes, if duplicates already exist | Clean up existing duplicates first, then add the constraint to prevent new ones |
Assuming corrupted data is isolated to the table where you noticed it | Referential integrity issues often cascade — a broken link can affect multiple related tables | Check related tables for downstream effects before considering the issue contained |
Fixing the visible bad data without investigating what wrote it in the first place | The same bug or process will likely keep producing bad data if left unaddressed | Identify and fix the root cause (often in application code), not just the current bad state |
Treating all inconsistencies as equally urgent | Can lead to rushing a fix on a low-impact issue while a more serious one goes unaddressed | Assess actual impact and urgency before deciding what to fix first |
How It Works
Step | What Happens |
1. Tell us what looks wrong | Share a specific example of the bad data and anything you know about when or how it started |
2. We assess the actual scope | Before changing anything, we determine how far the issue spreads — which tables, which relationships, how many records |
3. We fix it carefully, with recovery in mind | The fix is implemented in a way that's reversible wherever possible, especially for anything touching live production data |
4. We address the root cause | If the corruption traces back to a bug or a missing constraint, we help fix that too, so it doesn't keep happening |
5. We explain what happened and what was done | You get a plain-English rundown of the cause and the fix, useful for your own records and for preventing recurrence |
Why Codersarts
Data integrity issues carry real risk — a fix applied without understanding the full scope can turn a contained problem into a bigger one. We assess the actual state of your data carefully before making changes, across duplicate records, broken referential integrity, orphaned rows, and corruption stemming from failed migrations or application bugs. We fix both the current bad data and, where relevant, the underlying cause, so the same issue doesn't quietly reappear.
Turnaround Time
Scoped issues — a known set of duplicates, a specific broken relationship — are typically assessed and resolved within a day. Broader corruption, cascading integrity issues, or anything involving significant live production data is treated with more caution — we'll give you a clear timeline once we understand what's affected and the safest path forward.
FAQ
Question | Answer |
Is it safe to give you access to our production database for this? | We ask for the minimum access needed, and can work with read replicas or backups for initial assessment wherever possible before any live change. |
How do you make sure fixing this doesn't make things worse? | We assess the full scope first, favor reversible fixes, and confirm the plan with you before making changes to live data. |
Can you tell if our data is actually corrupted, or just looks unusual? | Yes — part of what we do is confirm whether something is a genuine integrity issue or expected, if unusual, data before recommending any fix. |
Will you also fix what caused the corruption, or just the data itself? | Where the cause is identifiable (a bug, a missing constraint, a bad migration), we address that too — fixing only the data without the cause usually means it recurs. |
Is this confidential if it's for a work project? | Yes. We don't contact your employer or client, and an NDA is available on request. |
Do you work with our specific database (PostgreSQL, MySQL, MongoDB, etc.)? | Very likely. We work across the major relational and NoSQL databases. |
Related Services
Migration & Schema Errors
Data Loss & Recovery
Data Synchronization Issues
Backup & Disaster Recovery Setup
Data Not Adding Up Right Now?
Stop before you make another manual change. Tell us what looks wrong and we'll help you assess the safest way forward.
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