Online Analytical Processing (OLAP)

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Online Analytical Processing (OLAP) is a computing approach designed for efficiently analyzing large volumes of multidimensional data from various perspectives. Unlike traditional Online Transaction Processing (OLTP) systems that handle day-to-day operations, OLAP systems are optimized for complex queries and data aggregations across multiple dimensions. These systems allow users to slice and dice data, perform drill-down and roll-up operations, and create pivot tables to gain insights from historical data. OLAP is particularly useful for business intelligence, financial reporting, and trend analysis. Modern OLAP solutions, such as Apache Druid or ClickHouse, can handle massive datasets and provide near real-time analytics capabilities. In the context of DuckDB, while it's not a traditional OLAP system, it offers OLAP-like functionality with its columnar storage engine and ability to efficiently process analytical queries on large datasets.