Data Vault Introduction


Course introduction
Centralized data warehouses are often designed using either the star model method (Kimball style) or normalized structures (Inmon style). Both methods have had to be reconciled with their original purpose. The Data Vault method developed by Dan Linstedt is specifically designed for the design of large centralized data warehouses (EDWs). The model has grown in popularity all over the world and e.g. In the Netherlands, most data warehousing is carried out using the Data Vault method. Data Warehouse and Big Data Guru Rick van der Lans says anyone planning a data warehouse needs to research the Data Vault method and then decide whether to implement it.

The Data Vault method is well supported for data warehousing, which requires integration of multiple data sources, flexibility of change, and easy scalability. The method has a clear and straightforward way to handle data history. In particular, the method has focused on data tracing and auditing, which has proved important e.g. as regulatory requirements become more stringent (so-called compliance requirements). Even if the method is not suitable as such, the course teaches a wide range of useful information about EDW strain modeling methods.

The course is well suited as an introduction to the Data Vault 2.0 certification course, which can be found in our calendar as held by Cindi Meyersohn.

The founder of our company, Ari Hovi, was the world’s first certified Data Vault modeler and Europe’s first Data Vault 2.0 Certified Practitioner. We also have a direct connection to Data Vault developer Dan Linstedt.


Data Warehouse – architectures and modeling
modeling methods suitable for different architectures
problems of star modeling and traditional ER data warehouse modeling
objectives for a good modeling approach

Data Vault method background
the history of the method
underlying ideas and architecture

Data Vault method building blocks
hubs, satellites and links
examples and instructions
stages of progress

Data processing and quality issues
where data is processed and managed
new ideas for quality management

Traceability and history
why traceability is important
traceability methods
methods of history

Evaluation of the Data Vault model

areas of application, problems and solutions
Products that support DW Automation and Data Vault
The role of Data Vault in broader modeling

Data Vault 2.0 features
hash key
Methodology, architecture and model
data virtualization
Hadoop articulation included

Daily start and end of the training event: training 9: 00-16.15.
Daily start and end of training event: training 9.00-16.15.

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“The course gave me a good idea of ​​what the Data Vault method is, even though I didn’t have any experience with that method before. There was a lot of discussion in the course, which sparked my own thoughts and ideas on ongoing projects. “It is worth taking part in the course, as the method can be applied in whole or in part to the modeled object. ”

“I wanted to expand the overall picture of the DV, also compared to other models. The best thing was the whole thing and the promised issue, my rating is 5/5. I recommend it!” Pasi Luoma-aho, Avarea Oy



CEO and Machine Learning / Artificial Intelligence lead at Ari Hovi

Hannu has been working with artificial intelligence for the first time in the mid-90s. He has a clear idea of ​​what is artificial intelligence today is realism, and what is advertising speech.

Hannu has assisted organizations in AI strategy work, from small organizations to the largest export companies, including the University Central Hospital Management Team and the Executive Committee responsible for AI strategy work at the TOP10 listed company.

He has trained heterogeneous groups from AI beginners to PhDs in machine learning to identify and work together on AI’s business opportunities.

Hannu also teaches SQL and Data Modeling.

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Data Vault Introduction

Data Control
1 day
Remote training

Koulutusohjelmalla / kurssilla ei ole aktiivisia aloituspäivämääriä, jos olet kiinnostunut kurssista ota yhteyttä.


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