Course Summary

The Data Modeler course is designed to provide a comprehensive understanding of data modeling techniques, tools, and best practices for designing robust and scalable data structures.

Whether you’re aiming to work in database management, data architecture, or analytics, this course equips you with the essential skills to model complex datasets and ensure data integrity in business environments. Students will gain hands-on experience building various types of data models, including conceptual, logical, and physical models.

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Introduction to Data Modeling:
- Importance of data models in business and IT
- Overview of data modeling levels (Conceptual, Logical, Physical)
Data Modeling Tools & Techniques:
- Overview of industry-standard data modeling tools (e.g., ERwin, IBM InfoSphere Data Architect)
- Use of Entity-Relationship Diagrams (ERDs), normalization, and denormalization techniques
- SQL for data modeling and schema design
Types of Data Models:
- Conceptual Data Modeling: Identifying entities and relationships
- Logical Data Modeling: Attributes, keys, and constraints
- Physical Data Modeling: Implementation in databases, indexes, and storage considerations
Relational vs Non-Relational Models:
- Relational database concepts (tables, joins, foreign keys)
- Introduction to non-relational models (document, key-value, graph databases)
Data Governance & Quality:
- Data consistency, integrity, and validation
- Metadata management and version control in data modeling
Advanced Topics in Data Modeling:
- Dimensional modeling for data warehouses (star, snowflake schema)
- Big data modeling strategies
- Designing for performance and scalability

Quizzes and Assignments:
- Regular quizzes to assess knowledge of data modeling concepts
- Hands-on tool assignments for creating ERDs and logical models
Individual Projects:
- Build and optimize a relational database model for a business use case
- Design a dimensional data model for a data warehouse
Group Project:
- Collaborate to create a complex data model incorporating relational and non-relational databases for a real-world scenario
Final Assessment:
- Comprehensive final project where students will model and implement a scalable database solution for a provided case study

By the end of this course, students will be able to:

Understand and explain the role of data models in information systems and business processes.
Design and implement conceptual, logical, and physical data models using industry-standard tools.
Analyze and create efficient relational and non-relational data models.
Apply normalization techniques to optimize data structures for performance and integrity.
Use data modeling to support data governance and ensure data quality.
Build data models for both OLTP (transactional systems) and OLAP (analytical systems) environments.
Work collaboratively on complex data modeling projects, solving real-world data challenges.

Regular & Intensive Learning Option

Class Schedule:
Morning Students – Monday to Thursday, 09:00 am – 03:00 pm
Afternoon Students – Monday to Thursday, 03:30 pm – 08:00 pm
Teaching Method: Online & Offline / Online only (eg. Google meet video call)
Course Duration: 2 sessions (6 months)
Session Length: 1 session = 3 months
DWTA Qualification: Academic Certificate
CTVET’s National TVET Qualification Framework (NTVETQF): National Certificate I
Tuition & Guidance Fees:
- Ghc 2600 per session or
- Ghc 900 per month

Slow-Paced & Relaxed Learning Option

Class Schedule:
Weekend Evening Students – Friday to Sunday, 06:00 pm – 08:00 pm
Teaching Method: Online & Offline / Online only (eg. Google meet video call)
Course Duration: 2 sessions (6 months)
Session Length: 1 session = 3 months
DWTA Qualification: Academic Certificate
CTVET’s National TVET Qualification Framework (NTVETQF): National Certificate I
Tuition & Guidance Fees:
- Ghc 2600 per session or
- Ghc 900 per month

Fill Application Form

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Database Modeler

Course Summary

Regular & Intensive Learning Option

Slow-Paced & Relaxed Learning Option

Ad CETECH Ghana

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