AI-assisted engineering
AI accelerates workload discovery, syntax conversion, dbt model scaffolding and documentation across recurring patterns.
PEOPLE / SYSTEMS / OUTCOMES
Build around the people who know the work.
FOCUSED ENGINEERING GUIDE
Move Oracle or Teradata workloads to Snowflake and dbt with evidence at every step.
A focused modernization path for schemas, SQL, stored logic and transformations, validated against the existing platform before migration.
Discuss your Snowflake migrationFORData platform leader, enterprise architect, migration program owner
TRIGGEROracle or Teradata workloads are moving to Snowflake, dbt or a cloud data architecture
WHAT THIS ENGAGEMENT COVERS
Oracle and Teradata to Snowflake Migration
Moving from Oracle or Teradata to Snowflake changes more than SQL syntax. Procedural logic, scheduling, utilities, data models and performance assumptions all influence how a workload should be redesigned on the target platform.
Ariftly begins with a dependency-aware assessment and groups the estate into migration waves. Repeatable conversions are accelerated, platform-specific exceptions are reviewed by engineers and target outputs are compared with the current system. The result is a Snowflake and dbt codebase accompanied by tests, lineage and a visible exception backlog.
THE PROBLEM
The difficult part is rarely the happy path.
We start with the dependencies, exceptions and verification burden that make this work risky.
- 01
Platform-specific SQL and procedural logic
- 02
Schedulers, utilities and dependencies outside the SQL repository
- 03
Monolithic jobs that do not map cleanly to dbt
- 04
Performance assumptions tied to the legacy platform
- 05
Migration progress measured by files rather than verified behavior
EXPECTED INPUTS
What we work from.
- Oracle or Teradata DDL and SQL
- PL/SQL, BTEQ or workload scripts
- Job and dependency inventory
- Reference datasets and outputs
- Snowflake and dbt standards
DELIVERABLES
What you receive.
- Workload and dependency assessment
- Target model and migration sequence
- Converted Snowflake SQL and dbt models
- Tests, lineage and documentation
- Source-to-target output comparison
- Exception and engineering-review backlog
DELIVERY PATH
A controlled path
to a verified result.
- 01
Assess
- 02
Sequence
- 03
Convert
- 04
Validate
- 05
Migrate
AI + DETERMINISTIC ENGINEERING
Move faster.
Verify the result.
Deterministic controls
Compilation, dbt tests, control totals, output comparisons and explicit exception review provide release evidence.
Accelerate repetitive work
AI assists analysis, classification, mapping and transformation where it can reduce manual effort.
Return inspectable artifacts
Your team receives code, mappings, tests, evidence and documented exceptions rather than a black box.
Fit the existing environment
We work with the systems, controls and deployment boundaries that already run the business.
Keep critical decisions human
Material changes and unresolved exceptions remain subject to accountable engineering review.
REFERENCE SCENARIO
Reference scenario: Oracle workload to Snowflake/dbt
A generic migration wave and review package. It illustrates classification and control points without inventing customer volumes or outcomes.
ARIFTLY / REVIEW PACKAGE
01 Object and dependency coverage
02 Snowflake and dbt conversion set
03 Unsupported construct register
04 Source-target comparison
05 Migration-wave acceptance pack
ENGAGEMENT MODEL
Start bounded.
Build from evidence.
- 01
Assessment
One bounded workload, system or partner flow.
- 02
Production work
Implement, integrate and validate the agreed scope.
- 03
Ongoing operation
Monitor, support or extend where the operating need justifies it.
- 04
Reusable automation
Turn proven repeated patterns into reusable engineering capability.
QUESTIONS
Can you migrate PL/SQL or Teradata BTEQ?
Yes, subject to assessment. Straightforward patterns can be converted systematically; procedural and utility-specific behavior may require redesign.
Does everything need to become dbt?
No. We choose boundaries based on maintainability, orchestration, performance and your target architecture rather than forcing all logic into one tool.
How is migration sequencing decided?
Dependencies, business criticality, workload complexity and validation readiness determine bounded migration waves.
Can you preserve current outputs during transition?
That is the purpose of the reconciliation plan. We compare agreed outputs and document intentional or unresolved differences.
Will you optimize Snowflake performance?
The engagement can include target-specific review, but performance goals and representative workloads must be defined explicitly in scope.
DISCUSS THE REAL PROJECT
Bring the system.
We’ll map the path.
Share a representative workload, specification or architecture. Sensitive production access is not needed for the first conversation.
Discuss your Snowflake migration