What Does In-Database Analytics Mean?
In-database analytics refers to a model of analysis where data processing is performed within a database to eliminate the overhead of moving large data sets to analytic applications. In such a model, the analytic logic is built into a database instead of in a separate application. Advantages of in-database analytics include parallel processing, scalability, analytic optimization and partitioning.
Techopedia Explains In-Database Analytics
An in-database analytics system contains an enterprise data warehouse integrated with an analytic database platform. In-database analytics is used in applications that require intensive processing, primarily because datasets and data marts are effectively consolidated in an enterprise’s data warehouse system, which facilitates and secures data analysis, processing and retrieval.
Advantages are as follows:
- Streamlines the identification of future business opportunities and risks, operational analytics, area trends and issues related to the exchange of data and information
- Improves an organization’s predictive analytics capability
- Provides ad hoc analysis reporting, allowing key users to create new reports and drill into data details, such as records and transactions
