The answer is the table’s role as a fact or dimension table, its size, and the choice of distribution key. These three factors directly determine how to minimize data movement during joins because Redshift distributes data across compute nodes, and mismatched join keys force large-scale data shuffling between slices. A large fact table should use KEY distribution on its join column to co-locate matching rows, while a small dimension table benefits from ALL distribution to avoid any movement at all. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of distribution trade-offs; a common trap is assuming EVEN distribution always reduces movement, but it actually increases shuffling for joined queries. Remember the memory tip: “Big KEY, small ALL, join columns for the call”—meaning large tables use KEY on the join column, small tables use ALL, and always align the distribution key with the most frequent join column to keep data movement to a minimum.
DEA-C01 Data Store Management Practice Question
This DEA-C01 practice question tests your understanding of data store management. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 is migrating a legacy data warehouse to Amazon Redshift. They need to choose a distribution style to minimize data movement during joins. Which THREE factors should they consider?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The size of the table (number of rows).
Option A is correct because the size of the table (number of rows) directly influences the distribution strategy. In Amazon Redshift, large tables benefit from a distribution style that evenly distributes rows across slices to avoid data skew, which can cause performance bottlenecks during joins. Choosing a distribution key that aligns with the join columns minimizes data movement, but the table size determines whether an ALL distribution (for small tables) or a KEY distribution (for large tables) is more appropriate to reduce shuffling.
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.
✓
The size of the table (number of rows).
Why this is correct
Large tables need careful distribution to avoid skew.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✓
The join frequency with other tables on specific columns.
Why this is correct
Joins on the same distribution key are collocated.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The number of columns in the table.
Why it's wrong here
Column count is not a primary factor for distribution.
✓
Whether the table is a fact or dimension table.
Why this is correct
Dimension tables often use ALL distribution.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The data type of the distribution key column.
Why it's wrong here
Data type does not affect distribution performance.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may overthink irrelevant table properties like column count or data types, while the core considerations for minimizing data movement are table size, join frequency, and table role (fact vs. dimension).
Detailed technical explanation
How to think about this question
Under the hood, Redshift distributes data across compute nodes using hash-based distribution (KEY), even distribution (EVEN), or full copy (ALL). During joins, Redshift performs collocated joins when distribution keys match, avoiding data redistribution across the network. A real-world scenario: a fact table with billions of rows joined frequently to a small dimension table (e.g., 1000 rows) should use ALL distribution for the dimension table to eliminate data movement entirely, while the fact table uses KEY distribution on the join column.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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 Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The size of the table (number of rows). — Option A is correct because the size of the table (number of rows) directly influences the distribution strategy. In Amazon Redshift, large tables benefit from a distribution style that evenly distributes rows across slices to avoid data skew, which can cause performance bottlenecks during joins. Choosing a distribution key that aligns with the join columns minimizes data movement, but the table size determines whether an ALL distribution (for small tables) or a KEY distribution (for large tables) is more appropriate to reduce shuffling.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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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