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Business Intelligence 2.0
Business Intelligence 2.0 (BI 2.0) is a development of the existing business intelligence model that began in the mid-2000s, where data can be obtained from many sources. The process allows for the querying of real-time corporate data by employees, but approaches the data with a web browser based solution. This is in contrast to previous proprietary querying tools that characterizes previous BI software. Overview The growth in service-oriented architectures (SOA) is one of the main factors for the development of BI 2.0, which is intended to be more flexible and adaptive than normal business intelligence. Data exchange processes also differ, with XBRL (Extensible Business Reporting Language), Web Services and various Semantic Web ontologies enable using data external to an organization, such as benchmarking type information. Business Intelligence 2.0 is believed to have been named after Web 2.0, although it takes elements from both Web 2.0 (a focus on user empowerment and community ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Business Intelligence
Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis and management of business information. Common functions of business intelligence technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics. BI tools can handle large amounts of structured and sometimes unstructured data to help identify, develop, and otherwise create new strategic business opportunities. They aim to allow for the easy interpretation of these big data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability, and help them take strategic decisions. Business intelligence can be used by enterprises to support a wide range of business decisi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linked Data
In computing, linked data (often capitalized as Linked Data) is structured data which is interlinked with other data so it becomes more useful through semantic queries. It builds upon standard Web technologies such as HTTP, RDF and URIs, but rather than using them to serve web pages only for human readers, it extends them to share information in a way that can be read automatically by computers. Part of the vision of linked data is for the Internet to become a global database. Tim Berners-Lee, director of the World Wide Web Consortium (W3C), coined the term in a 2006 design note about the Semantic Web project. Linked data may also be open data, in which case it is usually described as Linked Open Data. Principles In his 2006 "Linked Data" note, Tim Berners-Lee outlined four principles of linked data, paraphrased along the following lines: #Uniform Resource Identifiers (URIs) should be used to name and identify individual things. #HTTP URIs should be used to allow these thing ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
David Weinberger
David Weinberger (born 1950) is an American author, technologist, and speaker. Trained as a philosopher, Weinberger's work focuses on how technology — particularly the internet and machine learning — is changing our ideas, with books about the effect of machine learning’s complex models on business strategy and sense of meaning; order and organization in the digital age; the networking of knowledge; the Net's effect on core concepts of self and place; and the shifts in relationships between businesses and their markets. Career Weinberger holds a Ph.D. from the University of Toronto and taught college from 1980-1986 primarily at Stockton University (then known as Stockton State College). From 1986 until the early 2000s he wrote about technology, and became a marketing consultant and executive at several high-tech companies, including Interleaf and Open Text. His best-known book is 2000’s Cluetrain Manifesto (co-authored), a work noted for its early awareness of the Net as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Don Tapscott
Don Tapscott (born June 1, 1947) is a Canadian business executive, author, consultant and speaker, who specializes in business strategy, organizational transformation and the role of technology in business and society. He is the CEO of the Tapscott Group and the co-founder and Executive Chairman of the Blockchain Research Institute. He is the former Chancellor of his alma mater Trent University, and is currently an Adjunct Professor of Technology and Operations Management at INSEAD Business School. Career Tapscott has authored or co-authored sixteen books on the application of technology in business and society. His 2006 book, ''Wikinomics: How Mass Collaboration Changes Everything (2006)'', co-authored by Anthony D. Williams, was an international bestseller, was number one on the 2007 management book charts and has been translated into 20 different languages. Tapscott lives in Toronto. He is the former Chancellor of his alma mater Trent University, and is currently an Adjunct ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Synonym Ring
In metadata, a synonym ring or synset, is a group of data elements that are considered semantically equivalent for the purposes of information retrieval. These data elements are frequently found in different metadata registries. Although a group of terms can be considered equivalent, metadata registries store the synonyms at a central location called the preferred data element. According to WordNet, a ''synset'' or synonym set is defined as a set of one or more synonyms that are interchangeable in some context without changing the truth value of the proposition in which they are embedded. Example The following are considered semantically equivalent and form a synonym ring: foaf:person gjxdm:Person niem:Person sumo:Human cyc:Person umbel:Person Note that each data element has two components: # Namespace prefix, which is a shorthand for the name of the metadata registry # Data element name, which is the name of the object in each of the distinct metadata registry Ex ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Spreadmart
A spreadmart (spreadsheet data mart) is a business data analysis system running on spreadsheets or other desktop databases that is created and maintained by individuals or groups to perform tasks that can be done in a more structured way by a data mart or data warehouse. Typically a spreadmart is created by individuals at different times using different data sources and rules for defining metrics in an organization, creating a decentralized, fractured view of the enterprise. The concept was coined in 2002 by Wayne Eckerson at TDWI in his article ''Taming Spreadsheet Jockeys'', and intended pejoratively, as an undesirable system, which should be replaced by a data mart. However, critics such as Stephen Samild argue that spreadmarts have advantages over data marts and can be a desirable system. Problems Usually, spreadmarts grow where standard Business Intelligence (BI) reporting is too inflexible and too slow. A Business analyst uses the "export to Microsoft Excel" button in his BI ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Social BI
Social BI, or Social Business Intelligence, refers to the creation, publishing and sharing of custom business analytics reports and dashboards by end users of ''Cloud'' technologies. Social or collaborative BI is the use of Enterprise 2.0 tools and practices with business intelligence outputs for the purpose of making collective decisions. First enabled by the rapid growth of social media networks in 2009, Social BI allows for the collaborative development of post user-generated analytics among business analysts and data mining professionals. This has removed previous barriers to self-service BI while still employing traditional analytics applications. Social BI can also be interpreted as providing business intelligence based on social networks data. For example, a company selling consumer electronics goods needs to know how people are responding to their latest advertisements or promotions. The reports and visualizations made using social media represent what people are talking ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantic Wiki
A semantic wiki is a wiki that has an underlying model of the knowledge described in its pages. Regular, or syntactic, wikis have structured text and untyped hyperlinks. Semantic wikis, on the other hand, provide the ability to capture or identify information about the data within pages, and the relationships between pages, in ways that can be queried or exported like a database through semantic queries. Semantic wikis were first proposed in the early 2000s, and began to be implemented seriously around 2005. As of 2021, well-known semantic wiki engines are Semantic MediaWiki and Wikibase. Key characteristics Formal notation The knowledge model found in a semantic wiki is typically available in a formal language, so that machines can process it into an entity-relationship model or relational database. The formal notation may be included in the pages themselves by users, as in Semantic MediaWiki, or it may be derived from the pages or the page names or the means of linking. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantic Web Rule Language
The Semantic Web Rule Language (SWRL) is a proposed language for the Semantic Web that can be used to express rules as well as logic, combining OWL DL or OWL Lite with a subset of the Rule Markup Language (itself a subset of Datalog). The specification was submitted in May 2004 to the W3C by the National Research Council of Canada, Network Inference (since acquired by webMethods), and Stanford University in association with the Joint US/EU ad hoc Agent Markup Language Committee. The specification was based on an earlier proposal for an OWL rules language. SWRL has the full power of OWL DL, but at the price of decidability and practical implementations. However, decidability can be regained by restricting the form of admissible rules, typically by imposing a suitable safety condition. Rules are of the form of an implication between an antecedent (body) and consequent (head). The intended meaning can be read as: whenever the conditions specified in the antecedent hold, then the c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantic Grid
A semantic grid is an approach to grid computing in which information, computing resources and services are described using the semantic data model. In this model, the data and metadata are expressed through facts (small sentences), becoming directly understandable for humans. This makes it easier for resources to be discovered and combined automatically to create virtual organizations (VOs). The descriptions constitute metadata and are typically represented using the technologies of the Semantic Web, such as the Resource Description Framework (RDF). Like the Semantic Web, the semantic grid can be defined as "an extension of the current grid in which information and services are given well-defined meaning, better enabling computers and people to work in cooperation." This notion of the semantic grid was first articulated in the context of e-Science, observing that such an approach is necessary to achieve a high degree of easy-to-use and seamless automation, enabling flexible ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Relationship Extraction
A relationship extraction task requires the detection and classification of semantic relationship mentions within a set of artifacts, typically from text or XML documents. The task is very similar to that of information extraction (IE), but IE additionally requires the removal of repeated relations (other) and generally refers to the extraction of many different relationships. Concept and applications The concept of relationship extraction was first introduced during the 7th Message Understanding Conference in 1998. Relationship extraction involves the identification of relations between entities and it usually focuses on the extraction of binary relations. Application domains where relationship extraction is useful include gene-disease relationships, protein-protein interaction etc. Current relationship extraction studies use machine learning technologies, which approach relationship extraction as a classification problem. Never-Ending Language Learning is a semantic ma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ontology Alignment
Ontology alignment, or ontology matching, is the process of determining correspondences between concepts in ontologies. A set of correspondences is also called an alignment. The phrase takes on a slightly different meaning, in computer science, cognitive science or philosophy. Computer science For computer scientists, concepts are expressed as labels for data. Historically, the need for ontology alignment arose out of the need to integrate heterogeneous databases, ones developed independently and thus each having their own data vocabulary. In the Semantic Web context involving many actors providing their own ontologies, ontology matching has taken a critical place for helping heterogeneous resources to interoperate. Ontology alignment tools find classes of data that are semantically equivalent, for example, "truck" and "lorry". The classes are not necessarily logically identical. According to Euzenat and Shvaiko (2007),Jérôme Euzenat and Pavel Shvaiko. 2013Ontology matchin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
