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Data Migration

Safe, validated migration of legacy data into Reltio — including profiling, cleansing, transformation, and load with zero disruption to business operations.

What We Deliver

Data migration is one of the highest-risk phases of any MDM implementation. Poor planning, inadequate cleansing, or missed edge cases can result in bad data in your new platform on day one — undermining confidence and creating cleanup work that takes months to resolve.

Datagist's migration methodology is built around a simple principle: no data goes to production until it passes every quality gate. We use automated profiling, iterative cleansing, and multiple validation cycles to ensure your Reltio environment starts with clean, complete, accurate data.

Data Profiling
Data Cleansing
Data Transformation
ETL Development

By the Numbers

Records Migrated500M+
Avg. Data Quality Score98.5%
Zero-Downtime Migrations100%
Migration Projects40+

What We Deliver

A comprehensive set of capabilities delivered as part of every engagement.

Data Profiling

Comprehensive analysis of source data quality — identifying nulls, duplicates, format inconsistencies, and referential integrity issues.

Data Cleansing

Systematic remediation of data quality issues including standardization, enrichment, deduplication, and address validation.

Data Transformation

Map and transform source data structures to Reltio's canonical data model with full traceability.

ETL Development

Build robust extract, transform, and load pipelines with error handling, logging, and restart capability.

Validation & Reconciliation

Automated record counts, hash comparisons, and business rule validation to confirm migration completeness and accuracy.

Cutover Planning

Detailed cutover runbooks, rollback procedures, and parallel-run strategies to minimize go-live risk.

How We Deliver It

A structured, proven approach that minimizes risk and maximizes time-to-value.

01

Source Analysis

Profile all source data systems, document data structures, and identify quality issues that need remediation before migration.

Data ProfilingQuality AssessmentIssue Register
02

Mapping & Design

Create detailed source-to-target mappings, transformation rules, and cleansing logic for every data element.

Field MappingTransformation RulesCleansing Logic
03

ETL Development

Build migration pipelines with full error handling, logging, and the ability to re-run individual failed batches.

Pipeline BuildError HandlingLogging
04

Test Migrations

Run multiple test migration cycles — each one improving data quality — until all quality gates are passed.

Test LoadsQuality ChecksIssue Remediation
05

Production Cutover

Execute the final migration with real-time monitoring, immediate validation, and a clear rollback plan if needed.

Final LoadReconciliationSign-off

The Datagist Advantage

What sets our engagements apart from other Reltio consulting firms.

Quality Guaranteed

Multiple validation gates ensure only clean, accurate data reaches your production Reltio environment.

Zero Business Disruption

Parallel-run approach means your legacy systems stay live until you're fully confident in the migrated data.

Full Traceability

Every migrated record is traceable back to its source system — critical for audit and compliance.

Iterative Refinement

Multiple test cycles let us identify and fix issues before they reach production.

High Performance

Our ETL pipelines are optimized for high-volume migration — tested with hundreds of millions of records.

Comprehensive Documentation

Full migration runbooks, mapping documents, and reconciliation reports delivered with every project.

Common Questions

We log every quality issue found during profiling and work with your team to prioritize remediation. Some issues are fixed in the ETL transformation layer; others require source system cleanup. We provide a clear issue register with remediation recommendations.

Yes — most migrations involve multiple source systems. We design the migration architecture to handle multiple sources with conflict resolution logic when the same entity exists in more than one system.

Timeline depends on data volume, quality, and number of source systems. A typical migration runs alongside the implementation and adds 2–4 weeks of parallel effort.

We always have a tested rollback plan. Legacy systems remain available during cutover and we don't decommission them until the migrated data has been fully validated and accepted.

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Ready to Get Started?

Schedule a free consultation and let's discuss your data challenges.