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An OLAP cube is a multi-dimensional array of data. [1] Online analytical processing (OLAP) [ 2 ] is a computer-based technique of analyzing data to look for insights. The term cube here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three.
In computing, online analytical processing, or OLAP (/ ˈ oʊ l æ p /), is an approach to quickly answer multi-dimensional analytical (MDA) queries. [1] The term OLAP was created as a slight modification of the traditional database term online transaction processing (OLTP). [ 2 ]
An OLTP system is an accessible data processing system in today's enterprises. Some examples of OLTP systems include order entry, retail sales, and financial transaction systems. [5] Online transaction processing systems increasingly require support for transactions that span a network and may include more than one company.
The majority of Essbase users work with Essbase data via an add-in for Microsoft Excel (previously also Lotus 1-2-3) known as Smart View. The Essbase Add-In is a standard plugin to Microsoft Excel and creates an additional menu that can be used to connect to Essbase databases, retrieve or write data, and navigate the cube's dimensions ("Zoom in ...
The MultiDimensional eXpressions (MDX) language provides a specialized syntax for querying and manipulating the multidimensional data stored in OLAP cubes. [1] While it is possible to translate some of these into traditional SQL, it would frequently require the synthesis of clumsy SQL expressions even for very simple MDX expressions.
Graph databases differ from graph compute engines. Graph databases are technologies that are translations of the relational online transaction processing (OLTP) databases. On the other hand, graph compute engines are used in online analytical processing (OLAP) for bulk analysis. [5]
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Online analytical processing (OLAP) covers the analytical processing involved in creating, synthesizing, and managing data. With greater data demands among businesses, [citation needed] OLAP also has evolved. To meet the needs of applications, both technologies are dependent on their own systems and distinct architectures.
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