MLA-C01 Data Preparation for Machine Learning Practice Question
This MLA-C01 practice question tests your understanding of data preparation for machine learning. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company ingests daily log data into an S3 bucket. They need to update the existing ML training dataset with new data without reprocessing the entire history. Which two strategies should they adopt? (Choose two.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use AWS Glue to incrementally process new partitions
AWS Glue can perform incremental processing by using job bookmarks to track previously processed data and only process new partitions or files. This avoids reprocessing the entire historical dataset, making it efficient for updating ML training datasets with daily log data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Store all data in a single large file and use append operations
Why it's wrong here
Single files are not scalable and appending is inefficient for S3.
✓
Use AWS Glue to incrementally process new partitions
Why this is correct
Glue can process only new partitions using job bookmarks.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use a partition key such as date to add new partitions
Why this is correct
Partitioning allows efficient updates by only adding new data.
Related concept
Read the scenario before looking for a memorised answer.
✗
Manually copy new files to the same S3 bucket
Why it's wrong here
Manual processes are error-prone and not scalable.
✗
Overwrite the entire existing dataset with the new data
Why it's wrong here
Reprocessing all data is costly and unnecessary.
Common exam traps
Common exam trap: answer the scenario, not the keyword
AWS often tests the misconception that S3 supports append operations or that simply copying new files to the same bucket constitutes an incremental update strategy, when in reality S3 objects are immutable and a proper processing framework like AWS Glue with job bookmarks is required.
Detailed technical explanation
How to think about this question
AWS Glue job bookmarks work by storing state information about previously processed data in a persistent metadata store, allowing subsequent runs to skip already-processed partitions or files. When using a partition key like date (e.g., s3://bucket/logs/date=2025-03-01/), Glue can automatically discover new partitions and process only those, leveraging Hive-style partitioning for efficient incremental loads. This approach is commonly used in data lake architectures where daily log data is partitioned by date, enabling cost-effective and scalable ML pipeline updates.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Data Preparation for Machine Learning — This question tests Data Preparation for Machine Learning — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use AWS Glue to incrementally process new partitions — AWS Glue can perform incremental processing by using job bookmarks to track previously processed data and only process new partitions or files. This avoids reprocessing the entire historical dataset, making it efficient for updating ML training datasets with daily log data.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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