multidimensional databases, multidimensional queries, business intelligence, OLTP, OLAP, fact table, cube, dimension


Data warehouses are a collection of several databases, whose goal is to help different companies and corporations make important decisions about their activities. These decisions are taken from the analyses that are made to the data within the data warehouse. These data are taken from data that companies and corporations collect on daily basis from their branches that may be located in different cities, regions, states and continents. Data that are entered to data warehouses are historical data and they represent that part of data that is important for making decisions. These data go under a transformation process in order to accommodate with the structure of the objects within the databases in the data warehouse. This is done because the structure of the relational databases is not similar with the structure of the databases (multidimensional databases) within the data warehouse. The first ones are optimized for transactions on daily basis like: entering, changing, deleting and retrieving data through simple queries, the second ones are optimized for retrieving data through multidimensional queries, which enable us to extract important information. This information helps to make important decisions by learning which are the weak points and the strong points of the company, in order to invest more on the weak points and to strengthen the strong points, increasing the profits of the company. The goal of this paper is to treat data analyses for decision making from a data warehouse by using OLAP (online analytical processing) analysis. For this treatment we used the Analysis Services of Microsoft SQL Server 2016 platform. We analyzed the data of an IT Store with branches in different cities in Kosovo and came to a conclusion for some sales trends. This paper emphasizes the role of data warehouses in decision making.



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