“Online Analytical Processing” (OLAP)
The term “Online Analytical Processing” (OLAP) is an approach to computing that groups data into multidimensional structures to make it easier for users to access information and analyze the data from various angles. Business users can use it to run ad hoc queries and reports more quickly and carry out OLAP operations like slicing and dicing and drilling to find patterns, trends, and relationships between data sets.
Types of OLAP
ROLAP: Relational Online Analytical Processing is referred to as ROLAP. It stores data in columns and rows, retrieving the information at the user’s demand through queries. A ROLAP database can be accessed via complex SQL queries to calculate information. It can handle large data volumes, but processing times increase with the data size.
MOLAP: MOLAP is an acronym for Multidimensional Online Analytical Processing. MOLAP makes use of a multidimensional cube to access stored data. Due to its user-friendly interface, MOLAP is simple to use, even for new users. It is the best for “slicing and dicing” operations because of its quick data retrieval. MOLAP can only handle a certain amount of data makes it less scalable than ROLAP, which is a significant drawback.
Hybrid Online Analytical Processing or HOLAP comprises the functionalities of ROLAP and MOLAP servers. It provides the users with the ROLAP server’s scalability along with the MOLAP server’s speed of computation. The problem with HOLAP is the complex implementation or integration, as it supports both ROLAP and MOLAP.
Why is there a Need for OLAP?
More Significant Insights:
A company can predict future outcomes more accurately when more sample data is available for analysis. Instead of just viewing static data, businesses can view current data and perform “what if” analyses with OLAP operations.
Ad hoc Reporting:
Ad hoc analysis implies that analysts can ask questions and receive prompt answers from the OLAP system. There are fewer interruptions to the analyst’s thought process when there is no need to wait for data. Quick response times and intuitive, multidimensional data help them investigate trends they might miss.
OLAP organizes and analyses data using a multidimensional manner. Data is arranged in the form of dimensions, representing how business users typically think of the business. Business users, for instance, can view their data by market, product, and time.
Both business users and IT departments can benefit from an efficient OLAP solution. Business users can quickly and easily access centralized data for analysis. An OLAP solution helps the IT team by adding all data and business calculations to a data warehouse or database. This also reduces the burden on IT resources by empowering business users to conduct their analyses and reporting.Â« Back to Glossary