# Task Statement 3.5: Determine High-Performing Data Ingestion and Transformation Solutions

This study group focuses on **designing scalable and high-performing data ingestion and transformation solutions** using AWS services for real-time and batch processing.

We will follow **SecureCart**, an e-commerce platform, as they optimize **data ingestion, transformation, and visualization** to support **real-time analytics, data lakes, and machine learning workloads**.

***

### **📅 Study Group Agenda**

| **Week**   | **Topic**                            | **Key AWS Services**                                  |
| ---------- | ------------------------------------ | ----------------------------------------------------- |
| **Week 1** | Data Ingestion Strategies & Patterns | Amazon Kinesis, AWS DataSync, AWS Storage Gateway     |
| **Week 2** | Data Transformation & ETL Pipelines  | AWS Glue, AWS Lambda, AWS EMR                         |
| **Week 3** | Secure & Scalable Data Transfer      | AWS Transfer Family, AWS Snowball, AWS Direct Connect |
| **Week 4** | Building & Managing Data Lakes       | AWS Lake Formation, Amazon S3, AWS Glue Catalog       |
| **Week 5** | Data Visualization & Analytics       | Amazon Athena, AWS QuickSight, Redshift Spectrum      |
| **Week 6** | Hands-on Labs & Final Challenge      | Implementing a High-Performance AWS Data Pipeline     |

### **Final Study Group Summary**

| **Week**   | **Focus Area**                 | **Outcome**                                 |
| ---------- | ------------------------------ | ------------------------------------------- |
| **Week 1** | Data Ingestion Strategies      | Implement Streaming & Batch Ingestion       |
| **Week 2** | Data Transformation & ETL      | Process & Optimize Data for Analytics       |
| **Week 3** | Secure Data Transfer           | Securely Transfer & Migrate Large Data Sets |
| **Week 4** | Data Lake Architecture         | Build & Manage Scalable Data Lakes          |
| **Week 5** | Data Analytics & Visualization | Create Real-Time Dashboards & Insights      |
| **Week 6** | Hands-on Scenarios             | Implement a Scalable AWS Data Pipeline      |

***

### **🚀 Next Steps**

Would you like:\
✅ **Terraform automation scripts for AWS data pipelines?**\
✅ **Scenario-based quizzes for each study group session?**\
✅ **Instructor-led deep-dive discussions?**


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET 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.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.