OLAP operations and addition of aggregate functions in the food crops temporal data warehouse in Karo

Abstract

Yearly data recorded in an organization would lead to accumulation of the data. Many organizations now already use data warehouse technology to obtain more structured information. Data warehouse could help them in making decisions by analyzing historical data, but changes in the process of recording object data such as split and merge, would complicate search in the data warehouse. Currently there's already a developed data warehouse with temporal approach to address issues such as split and merge. This study improves food crop temporal data warehouse in Karo by adding OLAP operations. Implementation of OLAP in multidimensional data would make data analysis in the data warehouse easier for the user. OLAP operations which will be developed in this temporal data warehouse is slicing, dicing, drill down, and roll up process, and also aggregate functions. Key words: Temporal Data Warehouse, OLAP Operations, Aggregate Function.