Databases Reference
In-Depth Information
This trend is not new. Oracle began adding data warehousing features to Oracle7 in the
early 1990s. Ever since, additional features for warehousing and analytics appeared,
enabling better performance, functionality, scalability, and management. In addition to
the Oracle Database, Oracle offers tools for building and using a business intelligence
infrastructure, including data movement and data transformation tools, business anal‐
ysis tools and applications, and Big Data solutions.
A business intelligence infrastructure enables business analysts to determine:
• How a business scenario compares to past business results
• New business possibilities by looking at the data differently
• Possible future business outcomes
• How business actions can be changed to impact the future
This chapter introduces the basic concepts, technologies, and tools used in building data
warehousing and business intelligence solutions. To help you understand how Oracle
addresses infrastructure and analyzes issues, we'll first describe some of the basic terms
and technologies.
Data Warehousing Basics
Why build a data warehouse? Why is the data in an online transaction processing
(OLTP) database only part of a business intelligence solution? Where does Big Data fit
in a data warehousing deployment strategy?
Data warehouse relational database platforms are often designed with the following
characteristics in mind:
Strategic and tactical analyses can discern trends in data
Data warehouses often are used in creation of reports based on aggregate values
culled from enormous amounts of data. If OLTP databases were used to create such
aggregates on the fly, the database resources used would impact the ability to process
transactions in a timely manner. These ad hoc queries often take advantage of
computer-intensive analytic functions embedded in the database. Furthermore, if
data volumes of this size were entirely pushed to in-memory databases in a middle
tier, the platform cost would be prohibitive.
A significant portion of the data in a data warehouse is often read-only, with infre‐
quent updates
Database manageability features can make it possible to deploy warehouses con‐
taining petabytes of data, even where near real-time updates of some of the data is
occurring.
