Synthetic data only
Oracle Secure Data Engineering Lab
A portfolio environment that shows how I design, operate and secure Oracle-oriented data platforms: ingestion and transformation workflows, physical schema design, query tuning, recovery planning and governance evidence. Every figure on these pages is fabricated for demonstration.
Simulated fleet at a glance
Pipelines modelled
4
3 scheduled
Rows in demo history
5.5M
across recent runs
Run success rate
81.8%
healthy runs / total
SLA breaches
0
pipelines with a late run
Governance, replication and recovery signals
Data-quality score
75%
2 of 8 checks failing
Reconciled domains
3/4
source-to-target row and value match
Max replication lag
30.3m
2 channel(s) over budget
Backups verified
3/4
restore-validated, not exit-code only
Pipeline status board
Latest simulated run per workflow.
Database time profile
Synthetic wait-class distribution.
DB CPU42%
User I/O27%
Log file sync13%
Concurrency9%
Cluster5%
Other4%
What this lab demonstrates
ETL pipelines
Four modelled workflows with stage breakdowns, SLA tracking and run histories.
Schema & DBA
Partitioned fact tables, SCD2 dimensions, DDL and column classification.
Performance analysis
Plan reads, wait profiles and before/after tuning outcomes.
Resilience planning
RPO/RTO targets, drill outcomes and step-by-step recovery runbooks.
Data governance
Quality dimensions, reconciliation variance and domain classification.
Audit evidence
Privileged-action trail, denied attempts and the evidence packs behind them.
Architecture
Layered reference design plus the demo-versus-production boundary.
Security governance
Control catalogue covering access, secrets, tokenisation and retention.
Documentation & tests
Architecture notes, demo-vs-production boundary and the unit test suite.
3
Schema objects catalogued
4
Recovery scenarios rehearsed
7
Security controls tracked