With strategic planning your Data 360 insights deliver accurate, high-performance data visualizations for your business users. You can optimize your data processing with complex joins, relative time-windows, and advanced metric layering.
These considerations help you select the right aggregation methods and date and time dimensions to maintain a reliable source of truth within your segments. Use the guidelines in this section to build scalable, multi-dimensional insights that drive actionable customer intelligence.
- Define Relative Time-Window Metrics
Get real-time Data Cloud insights with metrics based on rolling time windows. Determine metrics using relative timeframes, such as a specified number of past seconds, minutes, or days. - Calculated Insights in Segmentation
Use a calculated insight to control data-driven insights in segmentation. You can also describe the calculated insight’s metrics and dimensions in a segmentation filter. - Using the Join Clause for Insights
A calculated insight can simultaneously access multiple data model objects (DMOs). A calculated insight query that accesses multiple rows of the different DMOs at one time is called a join query. Data 360 supports four types of joins in a calculated insight: inner, left, right, and full. - Metrics on Metrics
Organize complex Calculated Insights (CI) SQL data into logical steps and stitch powerful workflows. With metrics on metrics you can improve and reuse metrics for multiple scenarios. - Customer Data Subject Rights in Insights
A customer’s data subject rights relate to the storage and use of their personal data. When an insight uses the individual data model object (DMO), Data 360 automatically applies your customers’ data subject rights requests to the insight output.