A Data Migration Readiness Assessment (DMRA) for an Aimlux.ai consulting engagement is the "pre-flight check" that justifies the shift from a manual ETL project to a Migration-as-a-Product model. Using Equitus.ai DCS (powered by KGNN), the goal is to quantify the "Technical Debt" and "Risk Variance" of an Oracle-to-SAP/IBM DB2 move.
The following steps can be compiled into a digital costing analysis tool to provide a client with a tokenized migration as a service model.
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1. Inventory & Landscape Audit (The "Scope" Variable)
The primary cost driver in any migration tool is the sheer volume and complexity of the source data.
Database Object Count: Number of schemas, tables, and views in the Oracle environment.
Custom Code Identification: Quantifying stored procedures and triggers. (Manual migration costs scale exponentially here; DCS automates this via semantic mapping).
Data Volume Sizing: Total storage (TB/PB) to determine hardware requirements (e.g., IBM Power10 or Dell XR7620).
2. Semantic Complexity Scoring (The "Knowledge Graph" Variable)
Unlike standard "Lift and Shift," Equitus KGNN extracts facts and relationships.
Relationship Density: Assessing the "distance" between data points in legacy silos.
Unstructured Data Ingest: Evaluating the amount of PDF, JSON, or XML "document dumps" attached to Oracle records that need unification into the target system.
Redundancy & Cleansing Ratio: Identifying the percentage of "Cold" vs. "Hot" data to determine what actually needs to be moved to the high-performance SAP HANA/DB2 environment.
3. Risk & Compliance Variance
This section of the tool calculates the "Insurance Premium" of the migration.
Sovereignty Requirements: Is the migration happening on-premise due to HIPAA, SOX, or Defense regulations? (DCS on-prem minimizes the "Cloud Risk" cost).
Downtime Thresholds: Comparing the cost of a "Big Bang" migration vs. the DCS 30-day IOC / 60-day FOC rapid deployment model.
Data Provenance Audit: Calculating the cost to manually maintain an audit trail vs. the automated traceability built into KGNN.
4. Resource & GSI Labor Comparison
The costing tool must contrast the Aimlux SmartFabric model against a traditional Global Systems Integrator (GSI) project.
Manual vs. Automated ETL Hours: * Legacy: Estimated hours for a team of 10 data engineers over 12 months.
Aimlux: SKU-based pricing for DCS automated ingestion.
Training & Onboarding: Cost of training internal technical staff to manage the "living knowledge graph" post-migration.
5. Summary Table: Costing Tool Outputs
A professional assessment report would generate a table similar to this:
Job Titles: Oracle Database Administrator, Database Architect, Migration Architect, Head of Data Infrastructure.
Skills: PL/SQL, Oracle Database, Database Migration, SAP HANA, IBM Db2.
Groups: Oracle DBA Network, SAP S/4HANA Professional Group, IBM Power Systems.
|
Metric |
Traditional GSI Project
(Manual) |
Aimlux/Equitus DCS
(Automated) |
|
Timeline to IOC |
180–360 Days |
30 Days |
|
Full Go-Live (FOC) |
18+ Months |
60 Days |
|
Data Quality |
Raw Table Move |
Semantic Knowledge Graph |
|
Procurement Type |
T&M (Time &
Materials) |
Prepaid SKU |
|
Risk of Failure |
High (Due to manual ETL) |
Low (Productized
Migration) |
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