Any discussion on business intelligence architecture is intended for software architects or IT architects who are developing business intelligence applications. Business intelligence offers strategic benefits by means of transforming data into high value information.
The information of the organization will be placed into the right hands of people at the right time because if the company has a good data infrastructure in place. The broad term of business intelligence (BI) entails the applications, skills, practices, and technologies that make information more useful in order to support decision making. This concept can be clearly understood by looking at data infrastructure architecture.
The architecture presents how the organizational data is being processed to become useful information. In the past, organizational data was hard to keep and organize because of the lack of technology, more specifically the lack of a storage database where large amount of data could be kept for a long time.
A lot of changes happened due to the advancement of technology; organizational data can be kept and organized now using BI software and architecture. By using business intelligence architecture, IT architects have the basis or framework on how to manage the flow of data to become more useful for the organization.
The BI architecture usually presents solutions within a simple diagram, where the source of the data is determined. The source data comes from one or more databases, or even from third party data, such as industry data or census data.
All the organizational data can be stored into a storage database, called a data warehouse, which is a single relational database. The warehouse stays on an industrial-strength relational system. Microsoft’s SQL Server, Oracle, and IBM’s DB2 are considered to be industrial-strength relational systems. The organizational data will then pass through a multidimensional cube, which is a physical structure device that is organized to process queries. It is also a complex and an important data structure that involves data aggregations and security information determines who can access the data. The data in cubes will be compressed to lessen storage requirements. After passing through a MD cube, the organizational data will be accessed with the use of end-user tools and reports such as OLAP, static or live reports, balance scorecards, data mining, budgeting/forecasting, exceptions and notifications, and process input. All these applications, reports, and processes can be used to meet the requirements of end users.
Due to business intelligence technology, an organization is able to store its data into more powerful software that has a huge memory database, and can be accessed by end users through end-user applications or tools. The organizational data will then be used in further project implementation for the development of the organization.
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