Primary target platformsMicrosoft Fabric, Snowflake, Databricks
Common sourcesSQL Server, SSIS, SSAS, SSRS, Oracle, Teradata, Synapse, Azure Data Factory, Redshift, Glue, Informatica, Talend, DataStage, Alteryx, BigQuery, legacy ETL
Delivery modelSenior migration ownership, reusable source-to-target playbooks, AI-assisted execution, reconciliation-driven acceptance, controlled cutover and support
Entry offerMigration Wave 0 — Scope, Parity & Cutover Blueprint in ~10 business days, scope-dependent

Data Platform Migration

Move the platform. Keep the numbers the business trusts.

Senior-led migration from SQL Server, SSIS, Oracle, Synapse, Redshift and legacy ETL to Microsoft Fabric, Snowflake or Databricks. We combine platform-native migration tools, reusable playbooks and AI-assisted delivery to get the first reconciled workload live in weeks — with one team accountable through cutover and support.

SQL Server / SSIS / Oracle / Synapse / Redshift / legacy ETL Microsoft Fabric / Snowflake / Databricks

Current estate

SQL ServerSSISSSASSSRSOracleTeradataSynapseAzure Data FactoryRedshift & GlueInformaticaTalendDataStageAlteryxBigQueryLegacy ETL & flat files

3ALICA migration system

1. Inventory
2. Map
3. Convert
4. Reconcile
5. Cut over

Senior control gates at every step

Target platform

Microsoft Fabric
Snowflake
Databricks

AWS Redshift / S3 / Glue supported as a secondary route

15+ years

In data, DWH, BI & analytics

200+

Data, DWH & BI projects

40+

Delivery specialists

US & EU

Delivery footprint

The real risk

The hard part is not moving the data. It is preserving what the business already trusts.

Migration risk does not live in the tables. It lives in the logic and the meaning wrapped around them:

  • Business logic hidden in stored procedures and ETL
  • KPI definitions duplicated across BI, Excel and warehouse models
  • Undocumented downstream dependencies
  • Reports that must reconcile before legacy retirement
  • Parallel-run and cutover decisions
  • Security, lineage, performance and business acceptance
Migration paths

From the stack you need to retire to the platform you already chose.

Move to Microsoft Fabric

From

SQL Server, SSIS, SSAS, Synapse, ADF

To

Fabric Warehouse / Lakehouse, OneLake, Fabric Data Factory, Power BI

Best fit for a Microsoft-heavy estate with clear standardization and retirement triggers.

Move to Snowflake

From

SQL Server, Oracle, Teradata, Redshift, legacy ETL

To

Snowflake, dbt, modern ingestion, governed BI

Best fit when Snowflake is chosen but pipelines, modeling, reconciliation and retirement still need execution.

Move to Databricks

From

SQL Server / Synapse, Oracle / Teradata, Redshift / Glue, BigQuery, selected Snowflake

To

Delta Lake, Unity Catalog, Workflows, dbt, Databricks SQL

Best fit for fragmented analytics moving to a Lakehouse operating model.

Common source-to-target patterns

  • SQL Server / SSIS / SSAS → Snowflake
  • SQL Server / SSIS / Synapse → Microsoft Fabric
  • Oracle / Teradata → Snowflake or Databricks
  • Redshift / Glue or BigQuery → Databricks or standardized cloud
  • Informatica / Talend / DataStage / Alteryx → dbt, Fivetran, Airflow
  • Legacy BI & semantic models → Power BI or a governed semantic layer

Cross-cloud AWS migration is supported as a secondary route. We work from your chosen target architecture rather than pushing one vendor.

Where the work still is

Conversion is faster now. Business acceptance is still the hard part.

Snowflake, Databricks and Microsoft Fabric already automate meaningful assessment, conversion and validation work. What a client still buys is accountable execution across the parts that stay difficult after automated conversion:

  • Deciding what should migrate, modernize, or be retired
  • Remediating unsupported and business-specific logic
  • Rebuilding code target-native instead of copying technical debt
  • Report, KPI and business-rule parity
  • Coordinating business-owner acceptance
  • Dual run, rollback, cutover and decommissioning
  • Handover and a real support path
Delivery model

One execution chain, built for the first accepted workload — not a year of migration activity.

Traditional migrations split discovery, conversion, testing, reporting and cutover across teams and sequential handoffs. 3ALICA combines platform-native tools, reusable playbooks and AI-assisted production work under one senior-owned delivery chain, so the first bounded workload reaches business acceptance sooner.

Traditional delivery

  • Manual inventory and documentation
  • Large, handoff-heavy teams
  • Conversion first, validation late
  • Business logic rediscovered during UAT
  • Scope expands before the first workload proves value
  • Cutover becomes the first real end-to-end test

3ALICA delivery

  • Platform-native migration tools used where they are strongest
  • AI-assisted analysis, documentation, conversion and test generation
  • Reusable, source-to-target-specific playbooks
  • Senior-led architecture and wave planning
  • Conversion, documentation and testing running in parallel
  • Reconciliation gates built into every wave
  • Bounded first scope, cutover designed and tested from Wave 0

Faster because the repeatable work runs in parallel — not because controls are skipped.

How AI is used

AI-assisted execution. Senior-owned decisions.

AI-assisted production work

  • Estate and workload inventory
  • Dependency and code analysis
  • Documentation generation
  • Source-to-target mapping support
  • SQL and pipeline conversion assistance
  • Test generation
  • Reconciliation support
  • QA evidence and handover documentation

Senior-owned migration control

  • Target architecture
  • Business-rule and KPI parity
  • Security and compliance decisions
  • Exception remediation
  • Performance acceptance
  • Risk and rollback planning
  • Business sign-off
  • Production cutover
Engagement path

Start with one bounded wave. Scale after the numbers match.

Stage 1

Migration Wave 0 — Scope, Parity & Cutover Blueprint

~10 business days to an executable blueprint, scope-dependent

A fixed-scope, low-risk entry point that inventories the estate and produces a decision-ready first-wave plan.

Stage 2

First Reconciled Migration Wave

First bounded, production-ready, reconciled workload in ~4–8 weeks

One domain, one data mart, a group of SSIS packages, one pipeline family, one legacy database or one reporting domain — accepted on reconciliation, not opinion.

Stage 3

Scale, Cut Over, and Support

After the numbers match

Additional waves, controlled dual-run and cutover, legacy decommissioning, optimization, BI modernization, and managed platform support.

A blueprint, a first wave, and the entire migration are three different commitments. The first-wave timeline is not a promise to move an entire estate in 4–8 weeks.

Migration Wave 0

A decision-ready first-wave blueprint — not another strategy deck.

What you own after roughly 10 business days on a bounded mid-market estate (scope-dependent).

  • Source-estate inventory
  • Workload and pipeline inventory
  • Dependency map
  • Source-to-target mapping
  • Business-logic inventory
  • Critical KPI / report parity scope
  • Migration-wave plan
  • Target architecture recommendations
  • Reconciliation and acceptance approach
  • Security and compliance considerations
  • Cutover and rollback plan
  • Risk register
  • Effort range and first-wave statement of work

First-wave acceptance is based on

Data reconciliationBusiness-rule and KPI parityPerformance criteriaFailure / recovery testingBusiness-owner sign-offDocumented rollback or recovery logic
Why 3ALICA

Data roots. Product-grade engineering. A delivery model built for tighter mid-market budgets.

Data and BI roots

15+ years across data engineering, DWH, BI and operational analytics. Migration success means preserving business meaning, KPI definitions and reporting logic — not only moving bytes.

One execution chain

Software → integrations → data engineering → DWH / BI → QA → handover. Fewer boundary failures and fewer teams blaming one another.

Senior engineers own the decisions

The people who scope your estate and design the target architecture are the same seniors who own conversion exceptions, KPI parity and cutover — not a sales team that hands you to junior offshore delivery after signature.

Product-grade engineering discipline

Automated testing, observability, evaluation, orchestration and operating-cost discipline carried over from building production software and AI products.

Mid-market delivery economics

Focused senior pods, platform-native tools, reusable playbooks and AI-assisted production work make serious migration scopes viable without a Big Four-sized team or a bodyshop model.

Why now

Platform vendors now automate more assessment, conversion and baseline validation, so generic "AI-powered migration" positioning is weaker as differentiation. The remaining hard work — business-specific logic, target-native remediation, reconciliation, wave planning, acceptance, cutover, decommissioning and support — is where accountable execution matters, and tighter budgets make large sequential consulting teams harder to justify. Buyers need earlier proof before committing to a broad program.

After go-live

Go live without inheriting another unsupported platform.

Support is continuity and ownership, not lock-in. You own your cloud accounts, code, documentation and runbooks.

  • Post-cutover stabilization
  • Pipeline monitoring and incident response
  • Performance and cost optimization
  • Data quality and observability
  • Documentation and runbooks
  • Team enablement
  • Optional managed support
  • Follow-on BI, semantic-layer and integration work
Typical mid-market migration pattern

Legacy SQL Server / SSIS warehouse modern cloud data platform. Inventory dependencies, convert the first pipeline group, reconcile business outputs, run source and target in parallel, then cut over by domain.

Illustrative capability pattern, not a named customer engagement. For related delivery evidence, see our case studies.

Need migration delivery behind your client relationship?

3ALICA supports MSPs, data consultancies, cloud partners and systems integrators through co-presales, co-delivery, subcontracting or selective white-label execution. You keep the client relationship; we add migration depth and a senior-led delivery system.

See the Partner Delivery Model
FAQ

Migration questions, answered

Related capabilities

Need to improve the warehouse without re-platforming? See Data Warehouse Modernization. Moving applications, databases or infrastructure rather than the data platform? See Legacy Modernization.

Scope the first wave

Know what you are moving from and where you are going? Let us scope the first accepted wave.

Share the source platform, target platform, and the workload that cannot break. A senior data architect will review the fit and propose the smallest useful first step.

Email us directly

sales@3alica.com

Prefer email? Reach the same senior team at sales@3alica.com.