
Scalable E-commerce Data Pipeline with AWS Timestream & Glue
Optimizing E-Commerce ๐ with AWS: A Data-Driven Journey for Baby Clothing Platforms
๐ Order Trends: Purchase patterns over time.
๐ฆ Inventory Metrics: Stock levels and restocking schedules.
๐ Performance Metrics: Ensuring seamless user experiences.
- ๐ Serverless Architecture: No infrastructure management, so you can focus on business goals.
- ๐ Built-in Time-Series Functions: Simplifies trend analysis with features like smoothing and aggregation.
- โก High Performance: Fast queries on millions of records.
- ๐ฐ Cost Efficiency: Automatically moves older data to low-cost storage tiers.
- Write a Python Lambda function with boto3 SDK.
- Use time filters to fetch transactions from the last 24 hours.
- File Format: Nested JSON.
- Bucket Structure: Organized by
/year/month/day/
.
- ๐๏ธ Why Parquet? Reduces storage costs and query times.
- ๐ Steps: Flatten nested JSON, clean data, and handle null values.
- Why Grafana?
- Connects multiple data sources, including RDS and Timestream.
- Offers customizable dashboards for actionable insights.
- ๐ Use Case: Weekly sales trends visualization for marketing and inventory planning.
๐ Scalability: Seamless scaling for growing data volumes.
๐ธ Cost Efficiency: Managed and serverless services reduce overhead.
๐๏ธ Actionable Insights: Real-time dashboards enable data-driven decisions.