SAC live connections and calculations

Calculating with Live Connections: Unveiling the Potential and Limitations in SAP Analytics Cloud Stories

SAP Analytics Cloud (SAC) empowers users to derive valuable insights from real-time data through live connections. While the ability to perform calculations directly within SAC stories based on live connections is a significant advantage, it's crucial to understand the nuances and limitations involved. This article delves into the available calculation types, their restrictions, and best practices for optimizing performance.

Table of Contents

1. Introduction: Calculations in SAC Stories with Live Connections
   • The Power of Real-Time Calculations
   • Balancing Flexibility and Performance
2. Available Calculation Types: Empowering Story-Level Analysis
   • Story-Level Calculated Measures: In-Memory Flexibility
   • Restricted Measures: Focused Filtering
   • Calculated Dimensions: Transforming Dimension Members
   • Variance Calculations: Comparing Measures
3. Key Limitations: Navigating the Boundaries of Live Connection Calculations
   • Calculation Location: SAC vs. Source System
   • Functionality Restrictions: Formula and Feature Limitations
   • Performance Considerations: Impact of Complex Calculations
   • Data Blending Limitations: Single Source Focus
4. Performance Optimization: Strategies for Efficient Calculations
   • Pushing Calculations to the Source System: Best Practices
   • Simplifying Story-Level Calculations: Reducing Complexity
   • Leveraging Pre-Aggregated Data: Minimizing Processing
   • Understanding Query Performance: Monitoring and Tuning
5. Practical Examples and Use Cases
   • Simple Calculated Measure Example.
   • Restricted Measure Example.
   • Calculated Dimension Example.
6. Best Practices and Recommendations
   • When to Calculate in SAC vs. Source System.
   • Documentation and Naming Conventions.
   • User Training and Awareness.
7. Conclusion: Maximizing the Value of Live Connection Calculations

1. Introduction: Calculations in SAC Stories with Live Connections

• The Power of Real-Time Calculations:
  • SAC's ability to perform calculations on live data enables users to analyze and interpret information in real-time.
  • This empowers agile decision-making and provides immediate insights into changing business conditions.
• Balancing Flexibility and Performance:
  • While story-level calculations offer flexibility, it's essential to consider their impact on performance.
  • Understanding the limitations and optimizing calculations are crucial for achieving optimal results.

2. Available Calculation Types: Empowering Story-Level Analysis

• Story-Level Calculated Measures: In-Memory Flexibility:
  • Users can create calculated measures directly within SAC stories, using existing measures from the live connection.
  • These calculations are processed in SAC's in-memory engine, providing flexibility for ad-hoc analysis.
  • Example: Gross Profit = Revenue - Cost of Goods Sold.
• Restricted Measures: Focused Filtering:
  • Restricted measures allow users to filter existing measures based on specific criteria.
  • This enables focused analysis of specific subsets of data.
  • Example: Sales for Region = Sales filtered by region dimension.
• Calculated Dimensions: Transforming Dimension Members:
  • Calculated dimensions allow users to create new dimension members based on existing ones.
  • This can be useful for grouping or categorizing dimension members.
  • Example: Customer Size = If Revenue > $1M then "Large" Else "Small".
• Variance Calculations: Comparing Measures:
  • SAC supports basic variance calculations between measures, enabling users to compare performance over time or across different dimensions.
  • Example: Year over Year sales Variance.

3. Key Limitations: Navigating the Boundaries of Live Connection Calculations

• Calculation Location: SAC vs. Source System:
  • A fundamental limitation is that calculations performed in SAC stories are processed within SAC's in-memory engine, not pushed down to the source system.
  • This can lead to performance bottlenecks, especially for complex calculations on large datasets.
• Functionality Restrictions: Formula and Feature Limitations:
  • Not all formula functions available for imported data models are supported for live connections.
  • Complex calculations involving multiple data sources or custom currency conversions are not supported.
  • Limited use of advanced functions.
• Performance Considerations: Impact of Complex Calculations:
  • Calculations on live data can be significantly slower than those on imported data due to the processing overhead.
  • Complex calculations, especially those involving multiple steps or nested functions, can severely impact story performance.
• Data Blending Limitations: Single Source Focus:
  • Calculations cannot blend data from different live connections.
  • All calculations must be based on the single live connection that the story is based on.

4. Performance Optimization: Strategies for Efficient Calculations

• Pushing Calculations to the Source System: Best Practices:
  • Whenever possible, create calculations in the source system (e.g., within CDS views).
  • This pushes the processing workload to the source system, which is often more efficient.
• Simplifying Story-Level Calculations: Reducing Complexity:
  • Minimize the complexity of calculations performed in SAC stories.
  • Break down complex calculations into simpler steps.
  • Avoid nested functions when possible.
• Leveraging Pre-Aggregated Data: Minimizing Processing:
  • Use pre-aggregated data from the source system whenever possible.
  • This reduces the amount of data that SAC needs to process.
• Understanding Query Performance: Monitoring and Tuning:
  • Use the query monitor in the source system to identify performance bottlenecks.
  • Optimize queries and indexes in the source system to improve performance.

5. Practical Examples and Use Cases

• Simple Calculated Measure Example:
  • Create a calculated measure "Profit Margin" by dividing "Profit" by "Revenue."
• Restricted Measure Example:
  • Create a restricted measure "Sales in North America" by filtering the "Sales" measure by the "Region" dimension with a value of "North America."
• Calculated Dimension Example:
  • Create a calculated dimension that groups products into "High Value" and "Low Value" based on sales revenue.

6. Best Practices and Recommendations

• When to Calculate in SAC vs. Source System:
  • Calculate in the source system for complex, frequently used, or performance-critical calculations.
  • Calculate in SAC for ad-hoc, simple, or story-specific calculations.
• Documentation and Naming Conventions:
  • Document all calculations and use clear, consistent naming conventions.
  • This ensures maintainability and understanding.
• User Training and Awareness:
  • Train users on the limitations and best practices for calculations with live connections.
  • This empowers users to create efficient and effective reports.

7. Conclusion: Maximizing the Value of Live Connection Calculations

While calculations in SAC stories based on live connections offer valuable flexibility, it's crucial to understand their limitations and optimize for performance. By pushing calculations to the source system whenever possible, simplifying story-level calculations, and leveraging pre-aggregated data, users can maximize the value of real-time analytics in SAC. Through proper planning, documentation, and user training, organizations can effectively harness the power of live connections to drive data-driven decision-making.