Transform Raw Data into Clean, Normalized Output
Every custodian delivers data differently. FyleHub's visual rule builder maps, validates, and normalizes raw financial data to your internal schema — automatically, with zero custom code.
Visual Rule Builder
LIVEWhat Data Transformation Looks Like Today
Most teams still rely on brittle scripts and manual processes to normalize custodian data.
Manual Transformation
- ✗Copy-pasting custodian data into Excel mapping spreadsheets every morning
- ✗Custom Python scripts that break when a custodian renames a column
- ✗Inconsistent field names across sources — no single source of truth
- ✗No validation — bad records slip through to downstream systems silently
- ✗Format changes require developer time and emergency weekend fixes
FyleHub Transformation
- Visual rule builder — drag fields, set mappings, preview output instantly
- Automatic normalization runs on every ingestion without manual steps
- Validation on every record — bad data flagged before it reaches any system
- Custodian format changes absorbed automatically, zero developer time
- Every rule versioned, auditable, and rollback-capable at any time
Map, Validate, Normalize — Automatically
Define Field Mappings Visually
Use FyleHub's drag-and-drop rule builder to map source columns from any custodian to your internal target schema. No code, no spreadsheets. Each mapping is versioned and rollback-capable. When a custodian changes their format, update one rule — not twelve scripts.
- Drag-and-drop field mapping interface
- One-to-one, many-to-one, and derived field rules
- Supports every custodian format simultaneously
Field Mapping Interface
Source
Target
Validation Report
4,281
Records Processed
99.95%
Pass Rate
4,279
Passed
2
Flagged
Flagged Records
Every Record Checked Before Delivery
FyleHub validates every single record against configurable business rules — required fields, data types, range checks, referential integrity, and duplicate detection. Bad records are quarantined and flagged with specific reasons. Nothing invalid reaches your downstream systems.
- Configurable validation rules per source and field
- Quarantine and flag — never silently pass bad data
- Detailed error reports with row-level diagnostics
Messy Input Becomes Clean, Uniform Output
Custodians send dates in different formats, values with mixed decimal conventions, and security identifiers that don't match your internal codes. FyleHub normalizes everything — date formats, number precision, identifier resolution, currency codes, and encoding — into your exact target schema.
- Date, number, and currency format standardization
- Security identifier resolution (CUSIP, ISIN, SEDOL)
- Encoding and character set normalization
Before / After Normalization
Raw Input (3 custodians)
| date | value | id |
|---|---|---|
| 20260223 | 1,234,567.89 | 037833100 |
| 02/23/2026 | 1234567.89 | AAPL.OQ |
| 23-Feb-26 | 1.234.567,89 | US0378331005 |
Normalized Output
| as_of_date | market_value | security_id |
|---|---|---|
| 2026-02-23 | 1234567.89 | US0378331005 |
| 2026-02-23 | 1234567.89 | US0378331005 |
| 2026-02-23 | 1234567.89 | US0378331005 |
Every Transformation Type, Built In
FyleHub covers the full spectrum of data transformation operations required by institutional finance — from simple field renames to multi-source conditional logic.
| Spec | Detail |
|---|---|
| Rule Builder | No-code visual interface, drag-and-drop |
| Rule Versioning | Full version control with instant rollback |
| Validation Engine | Configurable per source, field, and data type |
| Processing Mode | Real-time streaming and batch |
| Enrichment Sources | Security master, FX rates, benchmarks |
| Audit Trail | Every transformation step logged, 7-year retention |
“Our four custodians all used completely different field names and formats. We were running Excel macros to reconcile them every morning. FyleHub eliminated that entirely — data arrives in our internal schema, ready to use, with a full audit trail for every mapping rule.”
— VP of Technology, $12B Asset Manager
Manual Work Eliminated
Full Rule Configuration
Scripts to Maintain
Frequently Asked Questions
QWhat is financial data normalization?
Financial data normalization is the process of converting data from different custodians — each with their own field names, formats, and encoding conventions — into a single, consistent schema. For example, BNY Mellon may call a field 'SecDesc' while State Street calls it 'SecurityDescription'. Normalization maps both to your internal field name 'security_name' so downstream systems receive consistent data regardless of source.
QCan we define our own labeling schemas and taxonomies?
Yes. FyleHub's data labeling engine is fully configurable. You define your internal taxonomy — account codes, asset class names, transaction type labels, benchmark identifiers, jurisdiction codes — and FyleHub maps all incoming data to your schema automatically, regardless of how each custodian structures the same information.
QWhat file formats can FyleHub produce as output?
FyleHub can deliver data in any format your downstream systems require: CSV, Excel, JSON, XML, XBRL, fixed-width text, Parquet, Avro, and fully custom formats. Each destination system can receive data in a different format — FyleHub applies the appropriate output transformation per delivery target.
QHow does data quality validation work?
FyleHub applies configurable validation rules at ingestion — required field checks, data type validation, range checks, referential integrity across datasets, and reconciliation against expected totals. When a record fails validation, it is flagged and quarantined before reaching downstream systems. Operations teams receive alerts with the specific failure reason and record details.
QHow long does it take to set up transformation rules?
Most clients have their core transformation rules configured within 15 minutes using the visual rule builder. Complex multi-source normalization across 5–10 custodians typically takes 1–2 days during the implementation window. Every rule is version-controlled and rollback-capable from day one.
Stop Wrestling with Inconsistent Data. Start Normalizing Automatically.
Book a 30-minute demo and see FyleHub transform your specific custodian formats into clean, unified output.
No custom code required · Setup in days, not months · No commitment