Accelerate Databricks Migrations in Weeks with Koantek’s X2D AI Accelerator

TL;DR: Migrate legacy EDW/ETL to the Databricks Lakehouse 3× faster with ~60% lower cost and near-zero risk. Koantek’s X2D automates ~80% of code conversion and validation, enforces Unity Catalog governance from day one, and delivers a production-ready Lakehouse in weeks—not years.

Why legacy migrations stall (and what it costs)

Rewriting decades of SQL and ETL by hand invites broken logic, overruns, and audit gaps. Dependencies are opaque, testing is manual (or missing), and teams rarely have deep skills on both the legacy stack and Databricks. The result: delays, dual-run costs, and shaky confidence. Leaders need a low-risk, high-speed path to Databricks that proves accuracy and compliance before cutover.

Meet X2D: “Anything to Databricks”

X2D is Koantek’s AI-powered migration factory (Brickbuilder Solution) that converts EDW, ETL, Hadoop/lakes, and analytics SQL to the Databricks Lakehouse—end to end:

• Assess → Plan → Transpile → Validate → Deploy
  
  
• AI agents scan, convert, and reconcile; humans review only the tricky bits.
  
  
• Governance, lineage, and auditability are built-in, not bolted on.
  
  

The 5-stage flow

1. Assess
   Auto-inventory schemas, ETL, and reports; complexity scoring; wave plan; ROI model in hours—not weeks.
   
   
2. Plan
   Dependency analysis and wave orchestration; staffing and timeline generated as code.
   
   
3. Transpile
   LLM-powered conversion of SQL dialects, stored procs, ETL workflows (Informatica/SSIS/DataStage/Talend) to Spark SQL, PySpark, Delta Live Tables, Lakeflow—with 80%+ automation.
   
   
4. Validate (Zero-Trust)
   Row-level reconciliation, query parity tests, performance checks; discrepancies logged and resolved to 99.9%+ accuracy before go-live.
   
   
5. Deploy
   Automated workspaces, pipelines, Unity Catalog objects/permissions, audit logs; optional parallel sync until decommission.
   
   

How X2D uses AI

• LLM transpiler fine-tuned on hundreds of migration patterns: typically ~85–90% auto-coverage for SQL/ETL constructs.
  
  
• Dialect mapping + vector search learns vendor quirks (Teradata BTEQ, Oracle PL/SQL, SAS, etc.) to produce Databricks-native equivalents.
  
  
• Human-in-the-loop for complex business logic with side-by-side diffs.
  
  
• ML-assisted reconciliation compares millions of rows deterministically; flags anomalies prior to cutover.
  
  
• Lakehouse Bridge integration pulls source metadata/lineage to inform optimal Lakehouse patterns.
  
  

Security, governance, and compliance by design

• Unity Catalog from day one: fine-grained access, lineage, tags, row/column masking.
  
  
• Multi-layer controls: SSO/MFA, cluster policies, secrets vaults, private networking.
  
  
• End-to-end encryption (at rest & in transit) and full audit logs of every migration action and downstream use.
  
  
• Alignment for HIPAA, GDPR/CCPA, PCI-DSS, Basel III, ISO/IEC 27001 with policy templates and PII handling baked in.
  
  

Outcomes you can forecast (and fund)

• ~60% lower TCO by eliminating legacy licenses/ops and optimizing cloud usage.
  
  
• 3× faster delivery (e.g., 8–12 weeks to first workloads; ~4–6 months for portfolios previously scoped at 12–18).
  
  
• ~80%+ automation of conversion + testing → fewer human hours, fewer human errors.
  
  
• ~10-week break-even typical via dual-run savings + productivity gains.
  
  
• Confidence to decommission legacy sooner, backed by reconciled accuracy and audit-ready controls.
  
  

Delivery model & timeline (prove, then scale)

• Assessment (2–3 days): Analyzer report—inventory, complexity, wave plan, ROI.
  
  
• Pilot (4–6 weeks): End-to-end migration of a critical slice; validate accuracy, performance, governance.
  
  
• Scale (8–12 weeks): Wave-based conversions at volume; production cutover; decommission plan; enablement & handoff.
  
  

Koantek backs timelines, accuracy, and governance with clear engagement SLAs and an outcomes mindset.

What X2D can migrate (the “Anything”)

• EDW: Teradata, Oracle, Netezza, Db2, SQL Server, Postgres, Redshift, Snowflake (and more).
  
  
• ETL/DI: Informatica, DataStage, SSIS, Talend, Airflow → Databricks Jobs/Lakeflow/DLT.
  
  
• Lakes: Hadoop/Hive/Cloudera, ADLS/S3 → Delta Lake.
  
  
• Analytics SQL: SAS/Cognos/BO/MicroStrategy extracts → Lakehouse SQL & views (BI semantic layer migration optional/roadmap).
  
  

Target landing zone: Databricks on AWS/Azure/GCP with Delta, Unity Catalog, MLflow, DABs—modernized, not just lifted-and-shifted.

See your path in days

• Free X2D Assessment: inventory, wave plan, and ROI in <1 week.
  
  
• Pilot: first workloads reconciled and serving from Databricks in 4–6 weeks.
  
  
• Scale: full migration executed with governance, accuracy, and cost transparency.
  
  

Email: sales@koantek.com