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XML for Analysis

XML for Analysis (XMLA) is an industry standard for data access in analytical systems, such as online analytical processing (OLAP) and data mining. XMLA is based on other industry standards such as XML, SOAP and HTTP. XMLA is maintained by XMLA Council with Microsoft, Hyperion and SAS Institute being the XMLA Council founder members.

History & Standards

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Research this topic

Explore the main themes, entities and connections around XML for Analysis. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

History

OLE DB for OLAPHyperion
2 related topics

API

MDXDMXSQLOLEDB
4 related topics

Overview

Online analytical processingData miningXMLSOAPHTTP
8 related topics

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

History

API

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

XML for Analysis

Nodes18
Edges17
Triples10
Avg. degree1.89
Density0.111111
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

xmla xml execute discover soap microsoft hyperion method command standard council industry mdx query session sas april joined properties rowset

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
XMLinstance ofXMLA is based on other industry standards0.80text
SOAPinstance ofXMLA is based on other industry standards0.80text
HTTPinstance ofXMLA is based on other industry standards0.80text
Timeoutinstance ofDMX or SQL.Properties - XML list of command properties0.80text
Catalog nameinstance ofDMX or SQL.Properties - XML list of command properties0.80text
etc.The result of Execute command could be Multidimensional Dataset or Tabular Rowset.DiscoverDiscover method was designed to model all the discovery methods possible in OLEDB including various schema rowsetinstance ofDMX or SQL.Properties - XML list of command properties0.80text
propertiesinstance ofDMX or SQL.Properties - XML list of command properties0.80text
keywordsinstance ofDMX or SQL.Properties - XML list of command properties0.80text
etcinstance ofDMX or SQL.Properties - XML list of command properties0.80text
etc.The result of Execute command could be Multidimensional Dataset or Tabular Rowsetinstance ofDMX or SQL.Properties - XML list of command properties0.80text

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.