Week 3-4: Data and Enterprise

The data landscape

Conceptual, logical, physical data models

The common problems with data

manageing data is a business issue

Case study：Banking / Healthcare architecture

Lab：Design a conceptual data architecture for a sample organization

Week 5-6: Data Modeling Foundations

Business rules and constraints

ER modeling

Normalization vs de-normalization

Common enterprise modeling pitfalls

Homework：Model an enterprise domain

Week 7: Metadata Management

Definition, types, roles of metadata

Operational vs business metadata

Metadata repository, catalog, data dictionary

Tools（Collibra / Alation introduction）

Semantic models + ontology basics

Lab：Build a simple metadata catalog

Week 8: Data Quality Management

Dimensions of data quality

Data profiling

Data cleansing strategies

Lab：Data profiling with open-source tools

Week 9-10: Data Governance

What is governance?

Governance vs management

Roles & responsibilities（Owner / Steward / Governance Board）

Policy framework

Data governance maturity models

Case Study：Evaluate a company’s data governance maturity

Week 11: Data Security & Privacy

Confidentiality / Integrity / Availability

Access controls

Data masking / anonymization

Ethical data usage

Week 12: Data Storage & Retention

Data retention policies

Backup / Disaster recovery

Lab：Set retention rules for a mock organization

Week 13: Big Data, Cloud & Modern Data Platforms

Data lake vs data warehouse vs lakehouse

Cloud-native data management principles

Data mesh vs data fabric

Week 14: Final Project Presentation

Enterprise Data Management Blueprint

Data architecture

Metadata & quality plan

Governance framework

Security & compliance

Implementation roadmap