> For the complete documentation index, see [llms.txt](https://awsinpractice.itassist.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://awsinpractice.itassist.com/study-group/aws-certified-solutions-architect-associate/domain-3/task-statement-3.5-determine-high-performing-data-ingestion-and-transformation-solutions/hands-on-labs-and-final-challenge.md).

# Hands-on Labs & Final Challenge

#### **Scenario:**

SecureCart’s engineering team must **implement a high-performance data ingestion and transformation solution**.

#### **Final Study Group Challenges:**

✅ **Scenario 1:** Implement a Scalable Data Ingestion Pipeline Using Amazon Kinesis\
✅ **Scenario 2:** Transform CSV Data into Parquet Format Using AWS Glue\
✅ **Scenario 3:** Optimize Data Transfer Using AWS Storage Gateway & Snowball\
✅ **Scenario 4:** Build a Data Lake Using AWS Lake Formation\
✅ **Scenario 5:** Visualize Business Performance Using Amazon QuickSight

🔹 **Outcome:** Learners **demonstrate AWS best practices for scalable and efficient data processing**.

***

### **📚 Recommended Study Resources**

✅ **AWS Well-Architected Framework – Data Analytics & Performance Pillars**\
✅ **AWS Glue, EMR, and Lambda for ETL & Data Processing**\
✅ **Amazon Kinesis & AWS DataSync for Data Ingestion**\
✅ **AWS Lake Formation for Secure Data Lakes**\
✅ **Amazon Athena, QuickSight & Redshift Spectrum for Data Analytics**