Smart Discovery

Let Smart Discovery analyze your data by running a machine learning algorithm to help you explore your data in a specific context, to uncover new, or unknown relationships between columns within a dataset.

In SAP Analytics Cloud, you can use Smart Discovery to clearly define the context of the business question you want to ask your data. To form the context, or topic of this business question, you must choose a target and an entity.

target: The Target is the measure or dimension you’d like to know more about.
entity: The Entity defines the dimension or dimensions you’d like to explore in relation to the target, and the level to which Smart Discovery must aggregate your data to analyze it for you. Within the dimension or dimensions you choose to define your entity, you can include all, or exclude some dimension members. There's no need for any data preparation. Simply select the Entity value from the Smart Discovery side panel.

Example

If you want to explore revenue by customer, you'd select 'revenue' as the Target, and 'customer' as the Entity.

Note

You can always ask more than one business question. Explore your data from different angles by asking Smart Discovery to analyze the same target in relation to different entities, and it produces different results.
You can use custom names for the target, target group, and the entity. The custom names you choose are then used instead of the default name, wherever they appear in Smart Discovery.

To narrow down the scope of the topic, or to optimize running Smart Discovery on large datasets, you can create filters to exclude specific records from dimensions in your model.

Smart Discovery always gives an overview of your data by automatically building charts to begin discovering more about your data. The generated content shows the target for the selected entity in relation to interesting or relevant dimensions and measures. Depending on the data you select to analyze, Smart Discovery can also show the influencers on the topic of the discovery, how they relate to one another, and key members or value ranges. Smart Discovery also alerts you if no significant or insightful relationships are present in your data.

Smart Discoveries are driven by users working on stories. You can exclude particular dimensions or measures from the analysis, focus on particular dimension members, and display relationships from a list of influencers. The Smart Discovery results can be saved as story pages that you can share within your organization.

Note

Currently, you can't run Smart Discovery on more than one million cells. By filtering the data first, you can reduce the number of cells included in your dataset. The number of cells is calculated by multiplying the number of measures by the number of records.

After running Smart Discovery, you can simulate numeric targets, using the results of the key influencer analysis. You can also view data records that are highlighted by the predictive model as being unexpected.