Chapter 3: Building Your First Aggregation Pipeline 

• Selecting a Collection: Begin by choosing the collection you want to aggregate data from. 
• Defining Stages: Plan out the stages of your aggregation pipeline, considering the order of operations. 
• Implementing the Stages: Use operators like `match`, `group`, and `project` in your pipeline. 

Chapter 4: Aggregation Expressions 

• Arithmetic Expressions: Perform mathematical operations on fields within documents. 
• String Expressions: Manipulate strings using functions like `concat` and `substr`. 
• Date Expressions: Perform operations on date fields, such as formatting and extracting components. 

Chapter 7: Real-world Examples 

• Sales Analysis: Use the Aggregation Pipeline to analyze sales data and calculate total revenue, average order value, and more. 
• Social Media Analytics: Explore how to aggregate social media data to find trending hashtags, user engagement metrics, and more. 

Chapter 8: Performance Considerations 

• Index Utilization: Design your pipeline to take advantage of indexes for faster query execution. 
• Memory Usage: Be mindful of memory consumption, especially when dealing with large datasets. 

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