Post by account_disabled on Feb 20, 2024 4:04:35 GMT -6
A multidimensional database The acronym OLAP comes from the English expression OLAP cube or On-Line Analytical Processing , used to designate data analysis systems based on multidimensional structures, or what is frequently called OLAP cubes . OLAP cubes are multidimensional structures (cubes) that allow you to analyze relational databases of large volume and variety with great agility and speed, greatly reducing the time and resources used in the analysis. OLAP cubes: basic concepts and functionalities There are different OLAP systems differentiated from each other, basically, by the types of databases on which they are built and which give rise, among others and mainly, to the following categories or systems: ROLAP systems : built on relational databases that mainly use snowflake or star schemas.
It is a system suitable for analyzing large volumes of data. olap cubes MOLAP systems : on this occasion the databases on which the OLAP engine works are multidimensional. It presents some advantages over the previous model, such as improving speed in data storage, optimizing cache memory performance, or efficiency in data USA Student Phone Number List extraction (due to the need for data to be previously processed or prestructured). ); However, it also presents some disadvantages, among others the risk of duplication in the analyzed data (especially when working with a certain number of dimensions), or the complexity of the process of loading the data into the databases due to what we mentioned a few years ago. moment (these must be treated or prestructured at the time of loading). HOLAP systems : they combine ROLAP (relational) systems with MOLAP (multidimensional) systems.
It is recommended to store the most recent data in MOLAP to improve the speed of the analysis, and the oldest or least used data in ROLAP, given the ease of storage. Having made this conceptual clarification, we must conceive of OLAP cubes as multidimensional databases composed of measures or dimensions , and created from the schemas of the tables used in relational databases (the tables, specifically their records, provide the measurements of the cubes, and their dimensions are determined by the dimensions of the boxes that each table has). We must keep in mind that cubes do not replace relational tables; They simply help to improve the efficiency, response speed and simplicity of queries , but they must always be supported by a relational model with previously normalized data. As we see, the architecture of the databases is a crucial issue for the correct use of OLAP cubes , an issue that, among others (such as the definition of the most pertinent data management policy, security management or other issues related to data warehousing).