DEA-C02 Data Movement Practice Question
A data engineer is tasked with migrating a 10TB historical dataset from an on-premise HDFS cluster to Snowflake. The data is currently stored in compressed CSV files. What is the most efficient strategy to ensure optimal performance during the initial bulk load into a Snowflake table?
⚠ Common exam trap
Candidates often believe that larger warehouses are always better, but they ignore the critical step of file-splitting. Parallelism depends on having enough individual files for the warehouse nodes.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Split the CSV files into sizes of 100-250 MB and use the COPY INTO command with a Large or X-Large warehouse.
For massive bulk loads, Snowflake recommends leveraging the COPY INTO command with a properly sized virtual warehouse to maximize parallel processing. Pre-splitting files into the 100-250MB range allows multiple threads across the warehouse nodes to ingest data concurrently. This approach avoids the overhead of serverless compute and provides more control over the ingestion window and resource utilization compared to continuous loading methods.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Upload the files to an internal stage and use Snowpipe with auto-ingest enabled to process the backlog.
Why it's wrong here
Snowpipe is designed for continuous, small-batch ingestion rather than massive historical bulk loads. Using it for 10TB of data can lead to higher costs and less predictable ingestion times because it lacks the massive parallel processing capabilities of a dedicated, large virtual warehouse configured specifically for high-throughput COPY operations.
- ✗
Execute a single COPY INTO command targeting the entire directory using an X-Small warehouse to minimize credit consumption.
Why it's wrong here
An X-Small warehouse provides limited compute resources and only a few parallel execution threads. For a 10TB dataset, this would result in an extremely long execution time and would not take advantage of Snowflake's ability to distribute the load across many nodes, potentially exceeding the maximum execution time for a single statement.
- ✓
Split the CSV files into sizes of 100-250 MB and use the COPY INTO command with a Large or X-Large warehouse.
Why this is correct
Dividing data into smaller files allows the virtual warehouse to utilize all available compute cores for parallel ingestion. Using a larger warehouse provides more nodes and threads, which significantly decreases the overall time required to load large datasets by distributing the I/O and processing load across the entire cluster.
- ✗
Use the Snowflake Web Interface (Classic UI) to upload the files directly into the target table in 50MB chunks.
Why it's wrong here
The web interface is intended for small, ad-hoc data uploads and is not suitable for terabyte-scale migrations. It lacks the automation, error handling, and high-performance throughput required for industrial-scale data movement, and the manual overhead of managing 10TB in 50MB chunks would be operationally impossible for a data engineering team.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
About these practice questions
One of 229 original DEA-C02 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Snowflake exam blueprint
This DEA-C02 practice question is part of Courseiva's free Snowflake certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C02 exam.