In Data Analyzer, users can perform various tasks to analyze their data, including filtering data and drilling down on data. Filtering allows users to narrow down the dataset to focus on specific subsets of data, enhancing the analysis's relevancy. Drilling down provides the ability to explore data at a more granular level, revealing deeper insights into the data points and trends within the larger dataset.
Reference:
SAP Analytics Cloud Help Documentation: Data Analyzer Usage
SAP Analytics Cloud User Guide: Filtering and Drilling Down in Data Analyzer

In SAP Analytics Cloud stories, conditional formatting can be applied to Table and Chart elements. This feature allows users to visually highlight data points based on specific conditions, such as thresholds, ranges, or comparisons, making it easier to identify trends, outliers, or areas of interest within the data presented in tables and charts.
Reference:
SAP Analytics Cloud Help Documentation: Conditional Formatting
SAP Analytics Cloud User Guide: Applying Conditional Formatting to Tables and Charts

To aggregate measures for columns such as Country, Region, City, and Customer Name as a single column in an embedded dataset, creating a level-based hierarchy is the most effective approach. This type of hierarchy allows you to define a multi-level structure that represents the logical relationship between different geographical entities and customer names. By doing so, you can easily perform aggregations and analyze data at various levels of detail, from the broadest level (e.g., Country) down to the most specific one (e.g., Customer Name).
Reference:
SAP Analytics Cloud Help Documentation: Creating Hierarchies in Models
SAP Analytics Cloud User Guide: Data Modeling and Hierarchies

When inputting new data for a private version in a story in SAP Analytics Cloud, it is necessary to "Publish" the data to ensure it is added to the model. Publishing the private version commits the changes to the underlying model, making the new data visible and accessible to other users according to their permissions. This step is crucial for ensuring that the updated data is incorporated into the shared model for further analysis and decision-making.
Reference:
SAP Analytics Cloud Help Documentation: Private Versions and Publishing SAP Analytics Cloud User Guide: Working with Private Versions in Stories