Data Warehousing
                     DATA 
WAREHOUSING
Introduction
• A data warehouse is a type of data management system that is 
designed to enable and support business intelligence (BI) 
activities, especially analytics. 
• Data warehouses are solely intended to perform queries and 
analysis and often contain large amounts of historical data. 
Source: www.oracle.com
Elements
• A relational database to store and manage data
• An extraction, loading, and transformation (ELT) solution for 
preparing the data for analysis
• Statistical analysis, reporting, and data mining capabilities
• Client analysis tools for visualizing and presenting data to 
business users
Source: www.oracle.com
Benefits of a Data Warehouse
• Data warehouses offer the overarching and unique benefit of 
allowing organizations to analyze large amounts of variant data 
and extract significant value from it, as well as to keep a 
historical record.
Source: www.oracle.com
Characteristics 
• Subject-oriented: They can analyze data about a particular 
subject or functional area (such as sales).
• Integrated: Data warehouses create consistency among 
different data types from disparate sources.
• Nonvolatile: Once data is in a data warehouse, it’s stable and 
doesn’t change.
• Time-variant: Data warehouse analysis looks at change over 
time.
Source: www.oracle.com
Common architectures
• Simple: All data warehouses share a basic design in which 
metadata, summary data, and raw data are stored within the 
central repository of the warehouse. 
• Simple with a staging area: Operational data must be cleaned 
and processed before being put in the warehouse. Although 
this can be done programmatically, many data warehouses add 
a staging area for data before it enters the warehouse, to 
simplify data preparation.
Source: www.oracle.com
Common architectures cont.
• Hub and spoke. Adding data marts between the central 
repository and end users allows an organization to customize 
its data warehouse to serve various lines of business. 
• Sandboxes. Sandboxes are private, secure, safe areas that 
allow companies to quickly and informally explore new 
datasets or ways of analyzing data without having to conform 
to or comply with the formal rules and protocol of the data 
warehouse.
Source: www.oracle.com
What is a Cloud Data Warehouse?
• A cloud data warehouse uses the cloud to ingest and store data 
from disparate data sources.
• The original data warehouses were built with on-premises 
servers.
Source: www.oracle.com
Advantages of cloud data warehouses 
• Elastic, scale-out support for large or variable compute or 
storage requirements
• Ease of use
• Ease of management
• Cost savings
Source: www.oracle.com
What is a Modern Data Warehouse?
• A modern data architecture addresses those different needs by 
providing a way to manage all data types, workloads, and 
analysis. 
• It consists of architecture patterns with necessary components 
integrated to work together in alignment with industry best 
practices. 
Source: www.oracle.com
Designing a Data Warehouse
• Any data warehouse design must address the following:
– Specific data content
– Relationships within and between groups of data
– The systems environment that will support the data warehouse
– The types of data transformations required
– Data refresh frequency
Source: www.oracle.com