With BI 2.0, data isn't stored in a database or extracted for analysis; BI 2.0 uses event-stream processing.
SOA provides a flexible and adaptive infrastructure, based two key principles - automation and virtualization.
Sharing information, thoughts, insight and best practices should be part of any organization's business intelligence solution.
SOA provides a flexible and adaptive infrastructure, based two key principles - automation and virtualization. It enables a flexible, composable and adaptive business integration environment. When used with semantic standards, a SOA based approach helps an organization get an integrated view of information across varied data-sets.
Open standards such as XBRL (Extensible Business Reporting Language) and various Semantic Web ontology enable use of data external to an organization, such as information for benchmarking.
The Semantic Web allows information and services on the web to be defined, making it possible for the system to understand and satisfy the requests of people and machines to use the web content. At its core, the semantic web comprises a set of design principles, collaborative working groups, and a variety of enabling technologies. These technologies are combined in order to provide descriptions that supplement or replace the content of Web documents. Thus, content may manifest as descriptive data stored in Web-accessible databases, or as markup within documents (particularly, in Extensible HTML (XHTML) interspersed with XML, or, more often, purely in XML, with layout or rendering cues stored separately).
" Semantic ontology allows systems to obtain more meaningful results and helps them to perform automated information gathering and research "
The machine-readable descriptions enable content managers to add meaning to the content, i.e. to describe the structure of the knowledge about that content. In this way, a machine can process knowledge itself, instead of text, using processes similar to human deductive reasoning and inference, thereby obtaining more meaningful results and helping computers to perform automated information gathering and research.
Metadata, simply put, is "data about other data". An item of metadata may describe an individual datum, or content item, or a collection of data including multiple content items and hierarchical levels, for example a database schema. Metadata provides information about, or documentation of, other data managed within an application or environment, such as data attributes, (name, size, data type, etc) and data structures (length, fields, columns, etc) and data linkages (where it is located, how it is associated, ownership, etc.).
Metadata allows users to transform enterprise data into knowledge. It is used extensively in BI 2.0 to support query based reporting, OLAP and business process management, providing:
To summarize, ‘metadata’ provides answers to the following questions: