This post introduces business intelligence (BI) and OLAP (online analytical processing) tools, explaining how they analyze data to provide insights into business performance through multidimensional analysis that breaks down measures like sales totals across dimensions such as time, geography, and product. It contrasts MOLAP systems, which use specialized pre-computed data stores for speed but require lengthy processing times, with ROLAP systems like Mondrian that query relational databases structured as star schemas, trading some performance for flexibility and ease of use. The post establishes that this series will focus on open-source ROLAP tools using MySQL, covering how they generate queries and handle aggregation to improve performance on large datasets.
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