Exploring SAP Analytics Cloud (SACE 11): Explaining Modeling Options
🎯 Objective
After this lesson, you’ll be able to differentiate between dimensions, models, and datasets in SAP Analytics Cloud.
📊 Key Concepts
🔹 Dimensions
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Categories used to slice and describe your data (e.g., Product, Region, Date, Customer).
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Can have properties (e.g., a Customer dimension can include phone number, address).
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Can be hierarchical (e.g., Year → Quarter → Month).
🔹 Measures
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Numeric values you analyze (e.g., Revenue, Quantity Sold, Profit).
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May be standalone or stored in an Account-type dimension (e.g., line items in a financial report).
Together, dimensions + measures = framework for data analysis.
🧩 Models
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Core data structures that combine dimensions and measures.
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Used as primary data sources for stories in SAC.
Two Types of Models:
| Type | Use Case | Write Access | Required Dimensions |
|---|---|---|---|
| Analytic | Reporting/Read-only analysis | ❌ No | None (Date is optional) |
| Planning | Planning, budgeting, forecast | ✅ Yes | Date & Version required |
📍 Created in the Modeler area, either:
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From imported data
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Or live data sources
📄 Datasets
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Lightweight, tabular collections of data used for quick exploration.
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Can be used to build stories without modeling effort.
Two Types:
| Type | Characteristics |
|---|---|
| Embedded | Lives only inside a story. Not reusable. Editable. |
| Public | Standalone. Shareable across stories. Cannot change data source. |
Limitations:
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Must re-import to refresh (no scheduling).
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Security is basic (access-level only, no column-level).
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Transformations are lost when converting to a model.
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Public datasets cannot be converted to models.
🔁 Conversions
| From | To | Notes |
|---|---|---|
| Embedded dataset → Public dataset | ✅ | Can’t change data source after conversion |
| Embedded dataset → Model | ✅ | Must redo transformations |
| Public dataset → Model | ❌ | Not supported |
📌 Comparison: Models vs. Datasets
| Feature | Models | Datasets |
|---|---|---|
| Governance | High (structured, secure) | Low (flexible, ad hoc) |
| Data Refresh | Can be scheduled | Manual only |
| Security | Fine-grained (e.g. per dimension) | Basic (file-level only) |
| Use Cases | Planning, enterprise reporting | Quick analysis, prototyping |
🧠 Key Takeaway
Use:
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Models when you need controlled, reusable, and secure data.
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Datasets for quick, story-specific exploration without the overhead of full modeling.
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