Question 575 of 1,730
Workload-Specific Database DesignhardMultiple SelectObjective-mapped

DBS-C01 Workload-Specific Database Design Practice Question

This DBS-C01 practice question tests your understanding of workload-specific database design. 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 large Oracle data warehouse to AWS. The warehouse contains 50 TB of data and runs complex analytical queries. The solution must support concurrency of up to 100 users and provide high performance for queries. Which THREE design decisions should the company make? (Choose three.)

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

Use distribution keys based on frequently joined columns

Distribution keys based on frequently joined columns ensure that related data is co-located on the same compute nodes, minimizing data movement across the network during joins. This is critical for complex analytical queries on large datasets in Amazon Redshift, as it reduces shuffle overhead and improves query performance.

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.

  • Use distribution keys based on frequently joined columns

    Why this is correct

    Distribution keys enable parallel processing and reduce data movement.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Design tables with columnar storage

    Why this is correct

    Columnar storage is efficient for analytical queries.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Use Amazon RDS for Oracle with Multi-AZ

    Why it's wrong here

    RDS is for OLTP, not analytical workloads.

  • Use Amazon DynamoDB with global tables

    Why it's wrong here

    DynamoDB is NoSQL and not suitable for complex analytical queries.

  • Use Amazon Redshift as the database engine

    Why this is correct

    Redshift is purpose-built for data warehousing and analytics.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates may confuse Amazon RDS for Oracle (an OLTP database) with a suitable data warehouse solution, overlooking that Redshift’s columnar storage and MPP architecture are specifically designed for large-scale analytical workloads.

Detailed technical explanation

How to think about this question

Amazon Redshift uses a massively parallel processing (MPP) architecture where data is distributed across multiple compute nodes. Distribution keys control how rows are distributed; choosing a key based on frequently joined columns enables collocated joins, avoiding the expensive redistribution of data across the network. Columnar storage in Redshift stores data by column rather than by row, allowing it to read only the columns needed for a query, drastically reducing I/O and improving compression ratios—especially beneficial for analytical queries that scan large subsets of columns.

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.

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FAQ

Questions learners often ask

What does this DBS-C01 question test?

Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Use distribution keys based on frequently joined columns — Distribution keys based on frequently joined columns ensure that related data is co-located on the same compute nodes, minimizing data movement across the network during joins. This is critical for complex analytical queries on large datasets in Amazon Redshift, as it reduces shuffle overhead and improves query performance.

What should I do if I get this DBS-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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Last reviewed: Jun 24, 2026

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This DBS-C01 practice question is part of Courseiva's free Amazon Web Services 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 DBS-C01 exam.