OLAP Database (Online Analytical Processing Database) is a type of database designed specifically for analysis of data from different angles. It uses a multidimensional data model to store data and can quickly crunch complicated queries on large amounts of data. It is built around an idea of pre-aggregated sets, making query processing faster and more efficient.
OLAP databases are often used to perform data analysis, such as forecasting, trend analysis, and what-if analysis. Data mining applications and predictive analytics are popular uses of OLAP databases. This type of database also allows for the discovery of additional information, such as from customer databases, allowing for personalized data and customer relationship management (CRM) strategies.
The most popular type of OLAP database is the multi-dimensional cube, also referred to as a multi-dimensional array. This multi-dimensional cube is used to store and analyze data across multiple dimensions. The dimensions of the cube are usually based on attributes of the data, such as time, customers, products, geographic locations, and other categories that provide insights into the relationships between the data points. The cube is visually represented as a cube, hence the name multi-dimensional cube.
OLAP databases are typically an integral part of a Business Intelligence (BI) system. BI systems allow for simpler analysis of data as well as generate reports for sales, marketing, and other functions. A OLAP database also allows for interactive exploration of data which is not possible with traditional databases.
In the end, an OLAP database is a powerful tool for extracting insights and trends from massive amounts of data. Using specialized analysis techniques, an OLAP database produces answers to tricky queries in moments that would have taken days to answer using traditional databases. It also allows for more personalized customer relationship management via accurate data mining that traditional databases cannot match.
