What is a key requirement for data fusion in Datorama?

Data fusion in Datorama involves combining data from various streams to create a unified view for analysis and reporting. A key requirement for this process is that data streams should share mutual values. This means that the different data streams need to have common attributes or identifiers that facilitate the merging of data into a cohesive whole. When multiple data streams share mutual values, it allows Datorama to align and correlate the information accurately, which is crucial for generating insights and ensuring data integrity throughout the fusion process.

By focusing on mutual values, organizations can leverage diverse datasets meaningfully, which enhances their analytical capabilities. Other requirements, such as a need for common IDs or originating from a single source, may not apply universally to all data streams, as Datorama is designed to handle complex data environments with various sources and structures. Thus, having shared attributes is essential for effective data fusion.