DEA-C01 Data Store Management Practice Question
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?
⚠ Common exam trap
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).
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
✓
The size of the table (number of rows).
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.
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.
- ✓
The join frequency with other tables on specific columns.
Why this is correct
Joins on the same distribution key are collocated.
- ✗
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.
- ✗
The data type of the distribution key column.
Why it's wrong here
Data type does not affect distribution performance.
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