Data Vault

WHAT’S IT ALL ABOUT?

Due to ever-increasing data volumes, it’s becoming ever more important to establish efficient methods for the collection and analysis of company data. The collection of such data allows strategic and operational business decisions to be made at a faster pace.

In this context, business intelligence (BI) and data warehouse (DWH) projects represent established procedures and processes that enable companies to systematically collect and evaluate electronic data. Due to ever-shorter update intervals and the increasing data volumes and levels of complexity in BI projects, the requirements placed on data warehouse systems are also expanding. Today’s systems must be able to respond to these requirements in a more flexible and agile manner than ever before.

While traditional modeling techniques such as 3NF and star schema often reach the limits of their capabilities during the creation of agile DWH projects, DataVault offers numerous advantages and overcomes these boundaries with ease.

Data Vault integrates and links business objects as a core element of data warehouse architecture. When modeling is carried out with Data Vault, all information about a business object is subdivided into a small number of completely separate entities:

Entity 1: Hubs
Hubs contain key information that uniquely identify an object.
(Examples of identities: customer numbers, item numbers)

Entität 2: Satellites
Satellites contain attributes that give a basic description of an object.
(Examples of attributes: customer names, item descriptions)

Entität 3: Links
Links contain information that describe the relationship between two or more entities.
(Examples of relationships: assignment of a customer to a customer type)

 

DATA VAULT RENDERS DATA WAREHOUSES FUTURE-PROOF

In traditional modeling methods, data is processed at the outset in order for it to be made comparable.

In contrast, with Data Vault, data is stored raw to begin with and only transformed accordingly at the end of the development chain.

 

Firstly, this brings the advantage that when a company changes their strategy, only a small part of the project must be reconfigured; there is no need for the entire project to be redesigned. Furthermore, it increases the manageability of data warehouse systems and guarantees easy system maintenance.

 

YOUR ADVANTAGES

Switching to Data Vault brings the following advantages:

• Unification of strategies for loading processes and selections
• Standardization and automation of data warehouse processes
• Enterprise-wide increase in efficiency and decrease in IT costs: data warehouses modelled on Data Vault are extremely scalable and have a flexible architecture. This combination of benefits allows companies to grow and change without being hindered by long development cycles, enormous costs and adverse effects on their existing data warehouse. As a result, data warehouses gain in efficiency, stability and controllability.
• Maximum transparency and traceability: All data remain traceable and verifiable at all times through comprehensive historicisation and holistic integration in hubs.
• Acceleration of data integration processes: division of entities into hubs, links and satellites, allowing the system to be populated independently for each of these entity types. As a result, data integration processes can be accelerated and loading times shortened, rendering the system suitable for big data and virtually real-time capable.

Need advice on making the switch to DataVault, or have unanswered questions? Get in touch with us today: