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Qlik's Associative Engine lets users do big data analytics, combining a number of data sources so that associations and connections can be formed across the data. [59] [60] The two main data analytics products, [61] [62] Qlik Sense (current cloud-based software) and QlikView (legacy on-premise product), serve different purposes running on the same engine.
A semantic layer maps complex data into familiar business terms such as product, customer, or revenue to offer a unified, consolidated view of data across the organization. By using common business terms, rather than data language, to access, manipulate, and organize information, a semantic layer simplifies the complexity of business data.
This page was last edited on 27 November 2018, at 13:21 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
Semantic search denotes search with meaning, as distinguished from lexical search where the search engine looks for literal matches of the query words or variants of ...
The Semantic Web Stack, also known as Semantic Web Cake or Semantic Web Layer Cake, illustrates the architecture of the Semantic Web. The Semantic Web is a collaborative movement led by international standards body the World Wide Web Consortium (W3C). [1] The standard promotes common data formats on the World Wide Web.
A semantic data model in software engineering has various meanings: It is a conceptual data model in which semantic information is included. This means that the model describes the meaning of its instances. Such a semantic data model is an abstraction that defines how the stored symbols (the instance data) relate to the real world. [1]
Action semantics [9] is an approach that tries to modularize denotational semantics, splitting the formalization process in two layers (macro and microsemantics) and predefining three semantic entities (actions, data and yielders) to simplify the specification;
Semantic networks are used in neurolinguistics and natural language processing applications such as semantic parsing [2] and word-sense disambiguation. [3] Semantic networks can also be used as a method to analyze large texts and identify the main themes and topics (e.g., of social media posts), to reveal biases (e.g., in news coverage), or ...
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