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Data Modelling
Published 12/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 40m | Size: 3.97 GB [/center]
Designing Structured, Scalable, and Efficient Data Models for Modern Systems
What you'll learn
Understand Data Modeling Concepts and Techniques
Design Effective Database Schemas
Apply Data Modeling Best Practices
Translate Business Requirements into Data Models
Requirements
Basic understanding of databases and data concepts, such as tables, rows, and columns.
Familiarity with SQL or basic querying concepts is helpful but not mandatory.
Understanding of business processes and data requirements to relate models to real-world scenarios.
Basic knowledge of relational database management systems (RDBMS).
Interest in database design, data architecture, or analytics.
Description
Data Modelling is a comprehensive course designed to equip learners with the skills and knowledge required to design, structure, and manage data effectively for modern applications and analytics. The course focuses on the principles, techniques, and best practices of data modeling, enabling learners to translate business requirements into accurate and scalable data structures.The course begins with an introduction to the fundamentals of data modeling, covering the different levels of models-conceptual, logical, and physical-and their significance in database design and data management. Learners explore entities, attributes, relationships, and constraints, gaining a clear understanding of how data components interact within a system. The course emphasizes normalization and denormalization techniques, helping learners design models that balance data integrity, efficiency, and performance.A significant portion of the course is dedicated to practical, hands-on exercises where learners create data models using industry-standard tools and apply them to real-world business scenarios. Topics such as relational databases, keys, indexes, and schema design are covered to ensure learners can implement their models effectively in database systems. The course also touches on advanced considerations, including handling complex relationships, optimizing models for analytics, and accommodating evolving business requirements.By the end of the course, participants will be able to design robust, flexible, and efficient data models that support applications, reporting, and analytics. This course is ideal for database developers, data analysts, business intelligence professionals, and anyone seeking to strengthen their ability to structure data in a meaningful and scalable way.
Who this course is for
The "Data Modelling" course is intended for data and technology professionals who want to design efficient, accurate, and scalable data structures to support applications and analytics
It is ideal for data analysts, database developers, BI professionals, and data engineers who work with data and need a strong foundation in data modeling principles.
well suited for software developers and system designers involved in application development who need to understand how to structure data effectively within relational databases.
Database administrators and IT professionals responsible for maintaining data integrity and performance will benefit from learning best practices in model design and normalization.
Data Modelling
Published 12/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 40m | Size: 3.97 GB [/center]
Designing Structured, Scalable, and Efficient Data Models for Modern Systems
What you'll learn
Understand Data Modeling Concepts and Techniques
Design Effective Database Schemas
Apply Data Modeling Best Practices
Translate Business Requirements into Data Models
Requirements
Basic understanding of databases and data concepts, such as tables, rows, and columns.
Familiarity with SQL or basic querying concepts is helpful but not mandatory.
Understanding of business processes and data requirements to relate models to real-world scenarios.
Basic knowledge of relational database management systems (RDBMS).
Interest in database design, data architecture, or analytics.
Description
Data Modelling is a comprehensive course designed to equip learners with the skills and knowledge required to design, structure, and manage data effectively for modern applications and analytics. The course focuses on the principles, techniques, and best practices of data modeling, enabling learners to translate business requirements into accurate and scalable data structures.The course begins with an introduction to the fundamentals of data modeling, covering the different levels of models-conceptual, logical, and physical-and their significance in database design and data management. Learners explore entities, attributes, relationships, and constraints, gaining a clear understanding of how data components interact within a system. The course emphasizes normalization and denormalization techniques, helping learners design models that balance data integrity, efficiency, and performance.A significant portion of the course is dedicated to practical, hands-on exercises where learners create data models using industry-standard tools and apply them to real-world business scenarios. Topics such as relational databases, keys, indexes, and schema design are covered to ensure learners can implement their models effectively in database systems. The course also touches on advanced considerations, including handling complex relationships, optimizing models for analytics, and accommodating evolving business requirements.By the end of the course, participants will be able to design robust, flexible, and efficient data models that support applications, reporting, and analytics. This course is ideal for database developers, data analysts, business intelligence professionals, and anyone seeking to strengthen their ability to structure data in a meaningful and scalable way.
Who this course is for
The "Data Modelling" course is intended for data and technology professionals who want to design efficient, accurate, and scalable data structures to support applications and analytics
It is ideal for data analysts, database developers, BI professionals, and data engineers who work with data and need a strong foundation in data modeling principles.
well suited for software developers and system designers involved in application development who need to understand how to structure data effectively within relational databases.
Database administrators and IT professionals responsible for maintaining data integrity and performance will benefit from learning best practices in model design and normalization.
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