XMLA stands for eXtensible Markup Language for Analysis. It is a language used in business intelligence (BI) and analytics to query, specify and manipulate the data in an Excel-like query, a feature of the Microsoft company's range of business intelligence and analytics products.
BI and analytics technology combines data, historical information and predictive analytics to analyse and provide insights on vast amounts of data. XMLA is used to supplement the language of Extract Transform Load (ETL), allowing it to access disparate data sources.
XMLA is a language of the analytics layer which queries underlying data sources such as SQL Server Analysis Services, Power BI and other data sources. The language is used to expose cubes and other data sources, combine heterogeneous data sources, and define the data structures used by the information layer.
XMLA is an open standard and is supported by many data sources. It acts as a middleware between the information layer and the data layer, and enables a wide range of data analysis, such as pivot tables, reporting and dashboard creation.
The language is written in an XML structure, which contains elements for defining the models and elements for returning the structured results. The language is used in both the cube definition, as well as in the data queries. Since it is written in an XML schema, it is easy to understand and modify.
XMLA is composed of various elements, and each element has a different purpose. Some of the phrases used in XMLA include Select, From and Where, just like a normal SQL query. Data cubes are also often referenced within XMLA statements.
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The elements in the language each have different characteristics and can be used in different situations. As an example, the Select element specifies what data to include in the query. Where and From elements are used to specify which subset of the data to query. The element is used to define the data being returned from the query.
XMLA also provides several functions, such as SUM(), COUNT(), AVG() and MAX(). These are used to perform calculations on the data and return the results. XMLA also provides a number of other useful features such as sorting and filtering data, categorising data and more.
When creating an XMLA query, it's important to consider the security, scalability, and performance implications. Depending on the data sources being queried, it may require the use of additional features such as user authentication, encryption, dynamic security and other security measures.
The language also has several advanced features, such as the ability to return subqueries, allow for the creation of advanced data models, perform calculations with multiple measurements and use custom functions to further enhance queries.
Due to the complex nature of XMLA, it is important to ensure that queries are optimised for the most efficient data retrieval. Guidelines such as ensuring that the optimum amount of data is retrieved, minimising the number of round-trips to the server, leveraging caching and other techniques to optimise the query process should be followed.