1. Data Ingestion
1.1. Real Time
1.1.1. IoT
1.1.2. Events/stream
1.1.3. Messages
1.2. Batch
1.2.1. Data Extraction
1.2.1.1. Database connectors
1.2.1.2. File based patterns
1.2.1.3. CDC
1.2.1.4. Replication
1.2.2. Data Transformation
1.2.2.1. ETL Patterns
1.2.2.2. ELT Patterns
1.3. Near real time
2. Data Management
2.1. Data Governance
2.2. Data Quality process management
2.3. Meta data - Business Glossary and Data Lineage
3. Data Models
3.1. Industry Reference Conceptual and Logical Models
3.2. Data Vault Modeling
3.2.1. Raw vault
3.2.2. Business Vault
3.3. Traditional techniques
3.3.1. Star Schema
3.3.2. Snowflake
4. Use Cases
4.1. Industry Specific Use Case
4.2. Customer Related use case
4.2.1. Single View of Customer
4.2.2. Customer Journey Event Store
4.2.3. Social Media Analytics
5. Data Consumption
5.1. BI Reporting / Dashboard
5.1.1. Data Preparation
5.1.2. Data Modeling
5.1.3. Data Visualisation
5.1.4. Analyse the data
5.1.5. Deploy & Maintain
5.2. Data Sharing
5.2.1. APIs
5.2.2. Downstream extracts
5.3. Data discovery
5.4. Cubes/OLAP
5.5. Data Virutalisation
6. Industry Sectors
6.1. Utility
6.2. Healthcare
6.3. Insurance
6.4. Automotive
6.5. Telecomm
6.6. Banking
7. Platform Architecture
7.1. Platform Architecture / Infrastructure
7.1.1. Azure
7.1.2. AWS
7.1.3. GCP
7.2. Data Security
7.2.1. Data Classification
7.2.2. Data Masking Patterns
7.2.3. Authentication
7.2.4. Authorisation
7.2.5. Network security
7.2.6. Data Encryption
7.2.7. Monitoring & logging
7.2.8. Data Privacy
7.3. Code Management
7.3.1. CICD
7.4. Infrastructure Management
7.4.1. Performance / Scale
7.4.2. High Availability / Fault Tolerance
7.4.3. Cost Management
7.4.4. IaC
7.4.5. Virtual Networks
8. Data Analytics
8.1. Machine Learning
8.2. Cognitive Services
8.3. Artificial Intelligence
9. Data Storage
9.1. Operational Data Store
9.2. Data warehouse
9.3. Data Hub
9.3.1. Reference Data Hub
9.3.2. Integration Data Hub
9.3.3. Analytics Data Hub
9.4. Data Lake
9.5. Data Lakehouse
9.6. Geospatial data store
10. Others
10.1. Decision trees
10.1.1. Rationale
10.1.2. Industry / Sector Specific
10.2. Design Patterns
10.3. Offerings
10.3.1. Hyper Scalers
10.3.2. Third Party
10.3.2.1. Informatica
10.3.2.2. Talend
10.3.2.3. Snowflake
10.3.3. On prem