Relational OLAP, or Relational On-Line Analytical Processing, is a type of multi-dimensional analytical system that is used in business intelligence. It is often used to analyze and quickly report on large datasets by assessing the relationships between different data points.
At the core of Relational OLAP is the OLAP Cube, which is a multi-dimensional array of data. This cube can be populated with warehouse data, from vendor databases and other relational data sources. Using sophisticated algorithms, users of relational OLAP can create different views of the data to draw useful insights from it.
The benefits of relational OLAP are many, but ultimately the big advantage it offers is speed. By using pre-calculated values on a multidimensional array, it allows queries to be executed much faster than if it were stored in a flat file, or even in a columnar format. This makes it suitable for running complex queries, and for use in decision-making.
Relational OLAP also allows for easier sharing and collaboration, since the data can be stored on a central server and accessed from a variety of different sources, such as desktop, laptop, and mobile devices.
In a business environment, Relational OLAP is an invaluable tool. It allows organizations to save time and money by making the data analysis process easier and faster. Additionally, it can help with trend analysis, identification of problems, and forecasting future results. As such, many organizations leverage relational OLAP technology for their business intelligence and decision-making needs.
