Concept Analysis Server
🔍 Key Features
📈 Statistical Analysis
Data Analysis Services uses statistical methods and models to analyse data and identify patterns, correlations or significance.
This includes descriptives, inferential statistics, regression analysis, time series analysis and more.
💼 Business Intelligence
Data Analysis Services helps management to extract business-critical insights that help improve business processes, optimise resources and identify new business opportunities.
💾 Big Data Analysis
In a world characterised by huge amounts of data, Big Data analysis is an integral part of Data Analysis Services.
Processing and analysing large and complex data sets require specialised tools and technologies.
🧩 Technologies
📡 XMLA (XML for Analysis)
XMLA provides a detailed specification for accessing analytical data sources.
This specification describes the structure of XMLA messages and the supported operations for accessing OLAP data sources.
The Test and Compatibility Kit (TCK) can be used to check compliance of different implementations with the XMLA specification and to ensure interoperability between systems.
Eclipse Daanse offers a Java API via Jakarta XML Bind and flexible customisable SOAP messages.
🧮 MDX (Multidimensional Expressions)
MDX is a query language for multidimensional data sources and is closely related to XMLA.
The scope and delimitation of MDX are as follows:
Strings can be converted into an implementation or API model using parsers.
📊 OLAP (Online Analytical Processing)
OLAP is a powerful technology widely used in data analysis and reporting.
It is based on several important components:
- DataCube Provider: Enables the creation and provision of multidimensional data cubes that offer efficient and flexible data organisation for complex analyses.
- Access and Security Model: Regulates access rights to data sources and ensures that only authorised users can access the information they need, while sensitive data remains protected.
- Calculation Model: Enables complex calculations and aggregations to be performed on the multidimensional data.
- Dynamic Function Model: Allows dynamic functions to be used to respond to changes in data sources or query results.
Parts of this implementation are a fork of the Pentaho Mondrian Project.
🗄️ Databases
Different databases can be integrated via JDBC (Java Database Connectivity), which allows developers to interact with different databases by providing a standardised method for connecting and querying.
The JDBC Database Dialect Abstraction Layer makes it possible to work with different databases without having to worry about the specific syntax differences.
OLAP data can thus also be accessed by means of OLAP database-schema mapping.
This section will be updated soon.