Khóa học Data Vault

Buổi 1

i. DWH introduction

1) The enterprise data warehouse environment
– Have a look on DWH aspects and challenges
– Fully DWH ecosystem & Data domains based on well-known international organization’ recommendation

2) Introduction to data vault
– History of data vault
– Overview components of Data Vault

3) Data warehouse architecture
– Kimbal’s DWH Architecture
– Inmon’s DWH  Architecture

ii. Scalable data warehouse architecture

1) Data vault 2.0 architecture
– Staging layer and attributes
– DWH Data vault layer and attributes
– Information Mart layer and attributes
– Soft and Hard business rules

2) Extension of data vault 2.0 architecture
– Metrics Vault
– Business Vault
– Operational Vault
– their attribute

iii. The data vault 2.0 methodology

1) Project planning
– Methodologies: SDLC, Agile/Scrum, Waterfall, CMMI, PMP, TQM, SigSixma
– Role & Duties involver
– Communication
– Project Estimation

2) Project execution
– Parallel Teams
– Agile Delivery

3) Review and improvement

Buổi 2:

iv. The data vault modelling

1) Data vault model
– Definition
– Appropriated selection amongst 3NF, Star Schema, Data Vault
DV 1.0 Concepts of:
– Hub
– Link
– Satellite

2) data vault 1.0
– Modelling and attributes
– Hub: Loading pattern
– Link: Loading pattern
– Satellite: Loading pattern
– ETL Job loading Data Vault 1.0 flow

3) Case study of Data vault 1.0, Hand-on Lab with MSSQL 2012 & above
– Implement Staging
– Implement Hub, Link, Satellite
– Implement Information Mar

4) data vault 2.0 modelling
– Modelling and attributes
DV2.0 Concepts of:
– Hub
– Link
– Satellite

5) Data vault 2.0 application
– Hub applications: Business key application
– Link applications: Link on link, same as link, hierachical link, computed aggregate link, exploration link, …, point in time & brigde table,…

6) Data vault 2.0 flexibility

Buổi 3:

v. The data vault implementation

1) Data vault 2.0 modelling case study

2) Data vault 2.0 load patterns
– Hub: Loading pattern
– Link: Loading pattern
– Satellite: Loading pattern
– ETL Job loading Data Vault 2.0 flow

3) Data vault 2.0 hash key

4) Data vault 2.0 parallel loading

5) Hand-on Lab with MSSQL 2012 & above
– Implement Staging
– Implement Hub, Link, Satellite
– Implement Information Mart

6) Case study and Hand on Lab with dbtVault Tool and Amazon Redshift intruduction and to be lab at the end day 2

vi. Dimensional modeling

1) Star schemas

2) Multi star schemas 

3) Dimension design 

Buổi 4:

vii. Master data management

1) Master data management architecture

2) Master data management development steps
– Profiling
– Standardization
– Matching
– Survivorship

viii. Meta data management

1) Meta data definition and types

2) Meta data capturing 

3) Meta data management Show-up with IBM Information Glossary Catalog/ Business Definition, Information Assets

ix. Multi-dimensional database

1) Introduction Multi-dimensional DB

2) Implement multi-dimensional OLAP on SSAS for Case Study 1

x. Data warehouse platform

1) Data vault 2.0™ technology landscape

2) Ibm data & analytics product overview

3) Aws data & analytics product overview

4) Case study and Hand on Lab with dbt Vault Tool and Amazon Redshift introduction and DEMO/ LAB