Data Vault Modeling Explained With Use Case
Learn Data Vault Modeling and design GDPR compliant data architectures. Solve scalability and agility issues with step-by-step processes and examples.
What you’ll learn
- Data Vault Modeling
- Data Modeling
- When to use Data Vault Model
- Problems with traditional OLAP Modeling
- Step By Step Data Vault Model Creation from a Business Case
- How to design a GDPR complaint Data Architecture using Data Vault approach
This is a beginner course for understanding Data Vault Modeling.
This course describes below topics
1) What is Data Vault : Generic Definition,
Data Vault is an agile system of business intelligence built to solve inadequacies in the Data Warehouse. Data Vault is one of the most popular methodologies when it comes to developing and maintaining a Data Warehouse.
2) What is the problem with traditional OLAP modeling i.e star schema : Problems such as scalability, non-agility, GDPR implementation.
3) How to resolve those problems with Data Vault Modeling.
4) Step by step process to create the data vault model.
5) Benefits of Data Vault, Drawbacks of Data Vault.
6) What is GDPR or General Data Protection Regulation?
General Definition GDPR outlines the specific rights that ensure individuals are in control of their personal data, can request a copy of their data at any time, and can ask for it to be deleted. GDPR will also mean individuals have to give consent before organizations can contact them – putting an end to random direct mail and companies selling data on to others.
7) Problems with implementing GDPR compliant data architecture.
8) Designing GDPR compliant data model using the data vault approach.
9) What is Business data Vault. Designing Bridge, PIT and Reference tables
10) When to use Data Vault Modeling and when not to use Data Vault approach.
11) Data Vault Modeling Tools
All the concepts mentioned above are explained in the course with examples.
After completing the course, the learner will be able to design data vault models and will be able to answers the above-mentioned points.
Who this course is for:
- Data Modelers,Data Architects,Data Analysts, Interview Preparation,Software Engineers,Students
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