What does "data transformation" involve in Oracle Analytics?

Data transformation in Oracle Analytics is fundamentally about preparing data for analysis. This process encompasses converting raw data into a format that is more conducive to gaining insights. It involves multiple tasks such as aggregating, normalizing, and restructuring data, which ultimately allows analysts to work more effectively with the information at hand.

Transforming data ensures that it is compatible with various analytical tools and techniques, facilitating meaningful analysis and decision-making. This is crucial because raw data can often be unstructured or not formatted in a way that aligns with the specific requirements of analytical processes. Therefore, data transformation is essential in ensuring that data not only meets the quality standards necessary for accurate analysis but also enhances its usability across various analytics applications.

While some might mistakenly suggest that data transformation focuses only on data cleansing or is about creating models from insights, these are limited aspects of the overall process. Similarly, sharing reports with stakeholders is an entirely different function related to the dissemination of analytical findings rather than the transformation of data itself. Understanding data transformation as a comprehensive process focused on preparing data efficiently is key to leveraging Oracle Analytics fully.