Data Vault Modelling : An Introductory Guide
Fentaw, Awel Eshetu (2014)
Fentaw, Awel Eshetu
Metropolia Ammattikorkeakoulu
2014
All rights reserved
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-201405137601
https://urn.fi/URN:NBN:fi:amk-201405137601
Tiivistelmä
The theme of this thesis is to prepare an introductory guide to Data Vault Modelling. The Data Vault is a relatively new method of modelling enterprise data warehouses. The Data Vault uses three core components to model an entire data warehouse. Thus it provides an easy alternate solution for data warehousing.
The thesis project was conducted by researching books, scientific journal articles, professional blog posts and professional community discussions. By doing so scattered information about Data Vault Modelling was gathered and analysed and compiled in to a guidebook. This paper could be used as a quick guidebook for those interested in finding information about Data Vault Modelling.
Data Vault is a relatively new solution to enterprise data warehousing. Although it introduces a better way of modelling enterprise data warehouses, it still has limitations when it comes to providing strict guidelines and handling unstructured text, semi-structured Doc Style data, XML and other data types which are broadly known as Big Data. These data types cannot be handled using the current approaches, tools and techniques; however there is an ongoing research to make the Data Vault Model be able to handle such Big Data. Thus this thesis includes only officially published articles about Data Vault.
The thesis project was conducted by researching books, scientific journal articles, professional blog posts and professional community discussions. By doing so scattered information about Data Vault Modelling was gathered and analysed and compiled in to a guidebook. This paper could be used as a quick guidebook for those interested in finding information about Data Vault Modelling.
Data Vault is a relatively new solution to enterprise data warehousing. Although it introduces a better way of modelling enterprise data warehouses, it still has limitations when it comes to providing strict guidelines and handling unstructured text, semi-structured Doc Style data, XML and other data types which are broadly known as Big Data. These data types cannot be handled using the current approaches, tools and techniques; however there is an ongoing research to make the Data Vault Model be able to handle such Big Data. Thus this thesis includes only officially published articles about Data Vault.