In-database analytics is a technology that integrates analytic capabilities directly within the database, eliminating the need to transfer data between the database and separate analytics applications. This technology is built within an enterprise data warehouse (EDW), which supports parallel processing, partitioning, and scalability optimized for analytics. In-database analytics is used for comprehensive processing, usually for fraud detection, risk management, and trend and pattern analysis.
In-database analytics boosts analytic capabilities by performing analysis where the data exists without moving it to separate analytics platforms. This takes advantage of the computational power of the database itself, reducing the load on other systems. In-database analytics is useful for statistics, predictive modeling, and data mining, where large volumes of data need to be processed. By processing the data directly in the database, data security is enhanced because the data never leaves the source.
