DEA-C01 Data Store Management Practice Question
A financial services company stores trade records in Amazon DynamoDB. An application performs many reads per second for individual trades by tradeId and also runs a nightly analytics job that must read every trade for a given trading day. The table uses tradeId as the partition key only. The nightly job currently performs a full table scan and is slow and expensive. The company wants to optimize the nightly access pattern with minimal application changes. Which change should the data engineer make?
⚠ Common exam trap
The trap here is thinking that a local secondary index can change the partition grouping, when it must reuse the base table partition key and therefore cannot group by trading day.
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
✓
Create a global secondary index with a partition key of tradingDay and a sort key of tradeId, then query that index for each day.
DynamoDB access is most efficient when queries target a specific partition key value. Because the base table partitions by tradeId, retrieving all trades for a day requires a Scan. A global secondary index partitioned by tradingDay gives each day its own logical partition, so the nightly job can use Query to read only that day's items. The base table schema and write path stay the same, so application changes are minimal.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add a local secondary index on the base table with tradeId as the sort key and query it for each day.
Why it's wrong here
A local secondary index must share the base table's partition key, which is tradeId, so it cannot group items by tradingDay. It only offers an alternative sort key within a single tradeId partition, which does not help retrieve all trades for a day. The correct grouping key must be the index partition key.
- ✓
Create a global secondary index with a partition key of tradingDay and a sort key of tradeId, then query that index for each day.
Why this is correct
A global secondary index with tradingDay as partition key groups all trades for a day into one logical partition, so the nightly job can issue efficient Query operations instead of scanning the whole table. Keeping tradeId as the sort key allows ordering and range access. The base table partition key and application writes remain unchanged, meeting the minimal-change requirement.
- ✗
Increase the table's provisioned read capacity units and schedule the full table scan during off-peak hours.
Why it's wrong here
Raising read capacity makes the scan faster only by consuming more capacity, and a Scan still reads every item and charges for all of them regardless of how few match the trading day filter. Cost scales with table size, so this does not meet the goal of an efficient, targeted access pattern.
- ✗
Enable DynamoDB Streams on the table and have the nightly job consume the stream to reconstruct the day's trades.
Why it's wrong here
DynamoDB Streams captures item-level changes with a 24-hour retention window and delivers them in near real time, not as a durable day-partitioned dataset. A nightly batch job would have to store and reshape stream records itself, adding significant engineering work and storage. It does not provide an efficient read pattern for querying a specific trading day.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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