Data modeling is still an important process—perhaps more important than ever before. But data modeling purpose and processes must change to keep pace with the rapidly evolving world of data. This course examines the principles, practices, and techniques that are needed for effective modeling in the age of big data.
Data architects; data modelers; database developers; data integrators; data analysts; report developers; anyone else challenged with the need to make structured enterprise data and non-traditional data sources work together.
Module 1 – Big Data Fundamentals
What is Big Data
Big Data Opportunities
NoSQL Technologies
Big Data Challenges
Exercise: Big Data Opportunities
Module 2 – Modeling and Data
Models
Modeling for Relational Storage
Modeling for Non-Relational Storage
Complementary Approaches
Exercise: Modeling Purpose
Module 3 – Key-Value Stores
Key-Value Stores Defined
Key-Value Data Representation
Use Cases
Examples
Exercise: Key-Value Pairs Modeling
Module 4 – Document Stores
Document Stores Defined
Document Data Representation
Use Cases
Examples
Exercise: Document Modeling
Module 5 – Graph Databases
Graph Databases Defined
Graph Data Representation
Use Cases
Examples
Module 6 – Embracing Big Data
BI Programs and Big Data
Human Side of Big Data
Tapping Into Big Data
Taking the Next Steps
Exercise: Embracing Big Data
Module 7 – Summary and Conclusion
Summary of Key Points
References and Resources
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