Types of Data
Warehouse Architecture
• Single-Tier Architecture: This type aims to
extract data in order to reduce the amount of data stored.
• Two-tiered Architecture: This type of
architecture aims to separate the actual Data Sources from the Database. This
enables Data Warehouse to expand and support multiple end users.
• Three-tiered Architecture: This type of
architecture has 3 phases in it. The section below contains Data Warehouse
Server Databases, an intermediate section of Online Analytical Processing
(OLAP) Server used to provide a vague view of Websites, and finally, the
advanced section Advanced Client Framework that includes tools and APIs used to
extract data.
The 4
components of the Data Warehouse.
1.
Database Warehouse Database
The
website forms an integral part of the Database. Database stores and provides
access to corporate data. Amazon Redshift and Azure SQL come under cloud-based
Database services.
2. Extraction, Transform, and Load
(ETL) Tools
All
activities associated with the extraction, conversion, and uploading (ETL) of
data in a warehouse fall under this category.
3. Metadata
Metadata
provides the framework and definitions of data, allowing for the creation,
storage, management, and use of data.
4. Database Access Tools
These Warehouse tools include Data Reporting
Tools, Data Inquiry Tools, Application Development Tools, Data Mining Tools,
and OLAP Tools.
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