Data Modernization & Legacy Data Migration
Our data modernization work moves business data off Access databases, aging applications, and unsupported platforms onto ones your team can support, report from, and use for AI. Data moves in stages and is checked against the old system before cutover, so the business keeps running.
Data checked before each cutover
- Access databaseAzure SQLLive
- ColdFusion appsPostgreSQLLive
- SpreadsheetsData warehouseMoving
- File sharesQueued
RECONCILIATION
Legacy system
Running until verified
What Is Legacy Data Migration?
Legacy data migration moves data out of old databases and applications, such as Microsoft Access, ColdFusion, FoxPro, or homegrown systems, into a platform that is supported and documented. The data has to keep its meaning on the way. Field formats, codes, and business rules buried in the old system must arrive intact.
Migration is one part of modernizing your data. The rest is cleaning it, connecting it to reporting and AI, and retiring the old system once the new one is verified.
Migration or modernization?
A migration copies data to a new home. Modernizing data goes further. The new platform gets a clear data model, validation, documented access, and pipelines that keep it current. A migration that skips those steps moves the old problems to a new server.
SIGNS
Signs Your Legacy Data Needs to Move
Legacy data rarely fails all at once. It gets harder to use and riskier to keep. These are the most common signs it's time to move it.
The database platform is unsupported
Core data lives in Microsoft Access, ColdFusion, or another platform your IT standards no longer support, so every fix is a workaround.
The developer who built it has left
The person who understood the tables, codes, and business rules is gone, and nobody wants to touch the system.
Spreadsheets fill the gaps
Staff keep side spreadsheets because the old system can't produce the reports or fields they need.
Other systems can't reach the data
The old database has no API, so reporting, other applications, and AI tools can't read it without manual exports.
Security falls short
Shared logins, missing access controls, and no audit trail leave sensitive records exposed.
A platform or contract is ending
A hosting contract, vendor platform, or old server is about to be retired, and the data has to move before access is lost.
OUR APPROACH
How We Approach Moving Legacy Data
We move data in stages, prove each stage against the old system, and keep the old system running until the new one is verified. Senior US-based engineers lead our builds, with nearshore support available for ongoing work.
Big-bang migration
- Everything moved in one weekend
- Hope that the data matches
- No way back if it doesn't
- Business rules lost on the way
Staged migration
Prove it on a representative dataset
We migrate a smaller, representative set of data first to prove the architecture before moving everything.
Reconcile before cutover
Each stage is checked against the old system, and differences are fixed before the next stage starts.
Keep a way back
Old and new run side by side until the new system is verified, so the business can switch back if something is wrong.
Carry the business rules over
Codes, calculations, and rules buried in the old system are documented and carried over, so the new data means what the old data meant.
MIGRATION APPROACHES
Choosing a Data Migration Approach
There are five common ways to move legacy data. Larger estates often use more than one.
| APPROACH | WHAT IT MEANS | WHEN IT FITS |
|---|---|---|
| Big bang | Move all the data at one cutover and switch off the old system | The data is small and simple, and the business can stop for the cutover |
| Phased | Move data in stages by module, region, or data set | Several systems or teams depend on the data |
| Parallel run | Run old and new side by side, kept in sync, until the new one is verified | The data supports daily operations and errors are costly |
| Sync and connect | Keep the old system and sync its data with the new one in both directions | The old system still runs a process that can't move yet |
| Archive and retire | Move historical records to low-cost storage and shut the system down | Few people use the data, but it must be kept |
How we choose the approach
We assess each source first: what data it holds, who uses it, how clean it is, and what depends on it. Most migrations combine approaches. Active operational data usually moves in phases or runs in parallel, and old history is often archived.
WHAT WE MIGRATE
Data We Modernize and Migrate
Our data migration services cover the sources companies most often need to move and the platforms they move to.
Microsoft Access databases
Access data moved to Azure SQL Server or PostgreSQL. For an industrial distributor and manufacturer, Access inventory data moved to Azure SQL, with a Microsoft Fabric data platform on top.
Legacy application databases
Data from ColdFusion, classic ASP, Visual Basic, and homegrown applications, migrated as part of legacy application modernization so the new application starts with complete records.
Database migration to cloud
On-premises and hosted databases moved to managed cloud databases such as Amazon RDS, Aurora PostgreSQL, and Azure SQL. For a bulk liquids shipping company, an automated tool migrated years of historical data from spreadsheets and a homegrown system into Amazon RDS. See cloud migration.
Two-way sync during a system change
Sync that keeps an old system and its replacement in step while processes move. For an environmental monitoring and compliance platform provider, we built a two-way sync between FoxPro and NetSuite on Azure.
Consolidated data platforms
Data from several legacy systems brought together in one place, ready for data engineering pipelines, reporting, and AI. For a federal agency, data from 29 ColdFusion and Access applications was consolidated into one PostgreSQL-backed application.
HOW IT WORKS
How a Legacy Data Migration Runs
A legacy data migration runs in six steps, and the old system keeps running until the new data is verified.
STEP 1
Assess sources
We inventory the data, its owners, its quality, and what depends on it.
STEP 2
Map and document
We map old fields, codes, and business rules to the new data model.
STEP 3
Pilot dataset
We migrate a smaller, representative dataset to prove the architecture.
STEP 4
Migrate in stages
Automated ingestion, transformation, and validation move the rest.
STEP 5
Reconcile
We compare old and new data and fix differences before cutover.
STEP 6
Cut over and retire
Users move to the new platform, and the old one retires once verified.
Avoiding downtime during the move
Old and new run side by side with data kept in sync, and users move in stages once the new data is verified. If something is wrong, the old system is still there. For a federal agency, JBS Dev kept the legacy applications running for their users through a three-year rebuild while their data moved into the new application.
What your team gets at handoff
You own the migrated data, the new data model, and the migration code. Services we can provide at handoff include documentation of the field mappings and business rules, knowledge transfer sessions, and support after cutover.
RESULTS
Data Migration Results
For a federal agency, JBS Dev consolidated 29 ColdFusion and Access applications into one application, migrated the legacy data into it, and kept the old applications running through the rebuild. For an industrial distributor and manufacturer, JBS Dev proved the architecture on a representative dataset before moving Access data to Azure SQL.
3 yrs
Of two-week sprints on one HR program
Government
Centralizing Legacy HR Applications for USDA FSIS
Challenge: HR systems more than 15 years old ran on ColdFusion and Microsoft Access, with almost no integration between them.
Result: One Python, Django, and PostgreSQL application replaced the agency's separate HR applications, and support calls dropped significantly.
Read the federal agency case study4
Systems unified into one data warehouse
Healthcare
One Data Warehouse for a Post-Acute Care Provider
Challenge: Four systems ran in isolation, and analysis depended on Excel pivot tables.
Result: A unified data warehouse with Tableau became one source of truth, with five legacy reports rebuilt and ten new ones added.
Read the post-acute care case study"JBS feels more like an extension of our internal team than a traditional vendor relationship."
Senior IT Leader, AmeriVet Partners
DATA VALIDATION
How We Check Migrated Data
Reconciliation is the step that makes a migration safe. It compares the old and new data, typically by record counts, totals, and samples of individual records, and each difference gets explained or fixed before cutover.
Older sources such as Access databases often hold duplicates, free-text codes, and records that break their own rules. Once verified, the data is ready for a data warehouse, BI reporting, and AI.
MIGRATE IN STAGES
Legacy database
Migration and checks
New platform
RECONCILE BEFORE CUTOVER
Old vs. new
Counts, totals, and samples compared
Cutover
After the data is verified
COST AND TIMELINE
What Drives Data Migration Cost and Timeline
Data migration cost and timeline depend mostly on how much data there is, how clean it is, and how many systems depend on it. Six factors drive most estimates:
- 01Number of source systems and databases
- 02Data volume and history
- 03Data quality and undocumented rules
- 04Systems and reports that depend on the data
- 05Downtime tolerance
- 06Security and compliance requirements
How the timeline is set
Timelines depend on the number of sources, the state of the data, and how long old and new must run side by side, and the assessment sets them. A pilot on a representative dataset comes first and gives a tested basis for the rest.
How cost is set
We don't quote a migration before we understand the data. The assessment turns the factors above into an estimate for each stage. Archiving old history instead of migrating it, or leaving a stable system in place and syncing with it, often lowers the total. We check that each stage pays for itself before recommending it.
ENGAGEMENT MODELS
Ways to Work With Us
Each model stands alone or leads into the next. Compare all the ways to work with us.
Assessment & Strategy
For companies that need clarity before committing to a build.
Start here if you're not sure what to change first. We review the system component by component, weigh difficulty against business impact, and recommend a path for each part, including what to leave alone. You get a roadmap you can act on with us or on your own.
- Technical assessment
- Architecture review
- AI opportunity mapping
- Modernization roadmap
- Prioritized recommendations
Best when: You need to understand the opportunity, risk, architecture, or roadmap before investing in a larger build.
Projects
For companies ready to build or modernize a defined system.
For a defined scope, senior engineers lead delivery from architecture through release. We work in stages, write tests for core components, and ship through CI/CD. You own everything we build, plus knowledge transfer and documentation tailored to your team.
- Modernization projects
- Custom applications
- Cloud platforms
- Data systems
- Integrations
- AI agents
Best when: You have a clear business problem, workflow, or platform that needs to be built, modernized, or connected.
Teaming / Managed Delivery
For companies that need experienced delivery capacity.
When you need more than a single project, services we can provide include architectural guidance for your existing team, hands-on development, QA, and ongoing support. Senior US-based engineers lead our builds, and nearshore support is an option for ongoing work.
- Senior-led teams
- Embedded engineering
- Ongoing development
- Knowledge transfer
- Flexible support
Best when: You need reliable engineering capacity, technical leadership, or ongoing delivery support without adding unnecessary management overhead.
Project stalled with another vendor? Software Project Rescue
WHY JBS DEV
How to Choose a Data Migration Partner
A migration partner should prove the data is right before you switch. Here are four questions to ask, and how we answer them.
- How will they prove the data is right?
- We reconcile old and new data at every stage and fix differences before cutover. A representative dataset goes first, to prove the architecture before the full move.
- What happens if something goes wrong at cutover?
- The old system keeps running until the new one is verified, so there is a way back. Users move in stages, and nothing is switched off until the new data checks out.
- Will the business rules survive?
- Yes. We map the codes, calculations, and rules in the old system to the new data model and document them. Where the original developer is gone, AI tools can help list rules from the code, and senior engineers confirm them.
- Where is the team?
- Senior US-based engineers lead our builds, with nearshore support available for ongoing work. From the first call, you will know exactly who is mapping, moving, and checking your data.
JBS Dev is a senior-led custom software development company, founded in 1999, that builds, modernizes, and integrates enterprise systems around the technology clients already own.
FAQ
Legacy Data Migration FAQs
What is data modernization?
Data modernization moves business data off aging databases and applications onto platforms that are supported, documented, and ready for reporting and AI. It includes migrating the data, and it also covers the new data model, data quality, access controls, and the pipelines that keep the data current. The old system retires once the new one is verified.
Is a data migration enough on its own?
Sometimes. If the data is clean and the new platform is already designed, a straight migration can work. Most legacy data needs more: a new data model, cleanup of duplicates and free-text codes, documented business rules, and pipelines into reporting. Moving it as it is relocates the old problems.
How long does a data migration take?
It depends on the number of sources, data volume and quality, and how long old and new must run side by side, and the assessment sets the timeline. A pilot on a representative dataset comes first, and it gives a tested basis for estimating the rest of the move.
How much do data migration services cost?
It depends on the number of sources, data volume and history, data quality, the systems that depend on the data, downtime tolerance, and compliance requirements. The assessment turns those factors into an estimate for each stage. Archiving history, or syncing with a stable system instead of migrating it, can lower the total.
Can we migrate without downtime?
In most cases, yes. Old and new systems run side by side with data in sync, users move in stages, and the old system stays available until the new data is verified. Some moves need a short, planned cutover window, and the assessment tells you which before the work starts.
Can you migrate Microsoft Access databases?
Yes. For USDA's Food Safety and Inspection Service, JBS Dev replaced separate ColdFusion and Microsoft Access HR applications with one central application on Django and PostgreSQL. We usually move a representative dataset first to prove the design, then migrate and validate the rest.
Should we move our database to the cloud?
Often, if the database runs on aging hardware or hosting your team can't support. Managed cloud databases such as Amazon RDS, Aurora, and Azure SQL handle backups, patching, and scaling. A database move works best when it's planned with the applications that use it. See cloud migration.
What happens to the old system after migration?
It keeps running until the new data is verified, then it retires. Historical records that are rarely used can be archived to low-cost storage instead of migrated. If the old system still runs a process that can't move yet, we can keep it and sync its data with the new platform until it can.
