A tailored course, built for your situation
Architecting Data Solutions for Modern Organizations
A tailored path from fragmented data to unified, scalable architecture
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Struggling to align data architecture with business velocity?
The situation this course is for
Data systems grow in complexity, but clarity shouldn’t be sacrificed. Outdated models create silos, slow decision cycles, and increase technical debt. For leaders like Marco, the pressure to deliver reliable, scalable data infrastructure, without over-engineering, is constant. This course answers the unmet need: practical, executable design that scales with purpose.
Who this is for
Technical founder and CEO driving data-first solutions in regulated, high-growth environments. Values precision, efficiency, and real-world applicability over academic theory.
Who this is not for
Entry-level analysts, non-technical stakeholders, or teams relying solely on off-the-shelf tools without customization needs.
What you walk away with
- Design scalable, secure data architectures aligned with business objectives
- Implement cloud-native integration patterns using AWS-native services
- Reduce time-to-insight by eliminating structural bottlenecks
- Govern data flows with automated, auditable frameworks
- Deploy a repeatable playbook for future system expansions
The 12 modules (with all 144 chapters)
Module 1. Foundations of Scalable Data Design
Establish core principles for building adaptable data systems. Covers separation of concerns, domain alignment, and long-term maintainability in cloud environments.
12 chapters in this module
- Defining data architecture scope
- Core AWS service mapping
- Identifying domain boundaries
- Data lifecycle phases
- Scalability trade-offs
- Security by design
- Cost-aware modeling
- Integration patterns overview
- Metadata fundamentals
- Versioning strategies
- Failure mode planning
- Architecture decision records
Module 2. Data Lake Patterns and Anti-Patterns
Distinguish effective data lake implementations from common failures. Focuses on partitioning, access control, and metadata rigor.
12 chapters in this module
- Lakehouse vs. warehouse decisioning
- Partitioning for performance
- Access layer design
- Metadata-driven discovery
- Schema evolution handling
- Data quality enforcement
- Cost control mechanisms
- File format selection
- Query pattern optimization
- Role-based access setup
- Audit logging integration
- Common failure scenarios
Module 3. Cloud-Native Integration Frameworks
Leverage AWS services to build resilient, event-driven pipelines. Emphasizes loose coupling, observability, and operational simplicity.
12 chapters in this module
- Event-driven architecture basics
- Kinesis vs. SQS selection
- Lambda execution models
- Step Functions orchestration
- Error handling design
- Dead letter queue patterns
- Monitoring integration
- Throughput tuning
- Cross-account flow setup
- Idempotency enforcement
- Payload size optimization
- Security token propagation
Module 4. Governance Without Friction
Embed compliance and data quality into workflows without slowing innovation. Covers policy-as-code and automated validation layers.
12 chapters in this module
- Policy-as-code foundations
- Data classification tagging
- Automated PII detection
- Access certification workflows
- Retention rule automation
- Audit trail generation
- Lineage tracking setup
- Cross-border compliance
- Role escalation paths
- Data ownership models
- Change approval workflows
- Policy testing frameworks
Module 5. Performance at Scale
Optimize query speed, reduce latency, and manage cost spikes in large datasets. Real-world tuning techniques for evolving workloads.
12 chapters in this module
- Query pattern analysis
- Indexing strategies
- Materialized view design
- Caching layer integration
- Data compaction routines
- Concurrency management
- Cost-per-query tracking
- Workload isolation
- Partition pruning
- Predicate pushdown
- Query execution plans
- Hot path identification
Module 6. Security Architecture for Data Systems
Design zero-trust data environments with layered defenses. Focuses on encryption, least privilege, and breach containment.
12 chapters in this module
- Zero-trust data model
- Encryption at rest
- Encryption in transit
- Key rotation policies
- IAM role design
- Cross-account access
- Network isolation
- VPC endpoint usage
- Data masking rules
- Audit log protection
- Incident response prep
- Threat modeling
Module 7. Metadata Management Strategy
Turn metadata into a strategic asset. Covers cataloging, lineage, and discoverability for enterprise-scale systems.
12 chapters in this module
- Metadata taxonomy design
- Automated harvesting
- Business glossary integration
- Lineage visualization
- Ownership assignment
- Staleness detection
- Search optimization
- API access patterns
- Change impact analysis
- Cross-system linking
- Versioned metadata
- Retention policies
Module 8. Data Quality Engineering
Embed quality checks at every layer. Covers anomaly detection, validation rules, and feedback loops for continuous improvement.
12 chapters in this module
- Data quality dimensions
- Rule definition syntax
- Automated validation
- Anomaly detection
- Feedback loop design
- Error resolution workflow
- Threshold calibration
- Historical drift detection
- Data profiling
- Root cause tagging
- SLA tracking
- Remediation automation
Module 9. Multi-Region and Hybrid Design
Architect for resilience and compliance across regions. Addresses data sovereignty, failover, and latency-sensitive workloads.
12 chapters in this module
- Region selection criteria
- Data residency rules
- Cross-region replication
- Failover testing
- Latency optimization
- Hybrid connectivity
- On-prem integration
- Bandwidth planning
- Consistency models
- Synchronization patterns
- DNS failover setup
- Monitoring across zones
Module 10. Cost Optimization Patterns
Reduce spend without sacrificing performance. Covers rightsizing, lifecycle policies, and monitoring for waste.
12 chapters in this module
- Cost allocation tags
- Resource rightsizing
- Spot instance usage
- Reserved capacity planning
- Storage tiering
- Query cost tracking
- Idle resource detection
- Auto-scaling policies
- Budget alerting
- Usage anomaly detection
- Lifecycle automation
- Cross-account billing
Module 11. Operational Excellence
Implement monitoring, alerting, and incident response tailored to data systems. Focuses on reducing toil and increasing reliability.
12 chapters in this module
- Monitoring scope definition
- Metric selection
- Alert threshold tuning
- Incident runbooks
- On-call rotation
- Post-mortem process
- Change tracking
- Deployment safety
- Rollback procedures
- Dependency mapping
- Automated recovery
- Toil reduction
Module 12. Future-Proofing Your Architecture
Design systems that evolve gracefully. Covers modularity, abstraction, and roadmap alignment for long-term success.
12 chapters in this module
- Modular component design
- Interface contracts
- Abstraction layers
- Roadmap alignment
- Technology horizon scanning
- Migration path planning
- Backward compatibility
- Deprecation strategy
- Stakeholder alignment
- Feedback integration
- Innovation budgeting
- Architecture review cycles
How this maps to your situation
- Building or refining a data platform on AWS
- Scaling existing pipelines without degradation
- Meeting compliance and governance demands
- Reducing operational cost and complexity
Before vs. after
Before
Data systems are fragmented, slow to adapt, and costly to maintain, governance feels like overhead, not enablement.
After
Architecture is unified, scalable, and self-documenting, governance accelerates delivery instead of slowing it.
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 3 hours per module, designed for integration into real-world projects as you progress.
If nothing changes
Without a structured approach, data complexity compounds. Technical debt grows, compliance risks increase, and teams spend more time fixing than building.
How this compares to the alternatives
Unlike generic cloud certifications or academic courses, this program delivers actionable patterns used in high-scale environments, focused on execution, not just concepts.
Frequently asked
Is this course specific to AWS?
Yes, content is tailored to AWS-native services and design patterns used in real-world deployments.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Are there video lessons?
No, the course is text-based with downloadable templates and practical examples for immediate use.
$199 one-time. Approximately 3 hours per module, designed for integration into real-world projects as you progress..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours