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Design and implement data storageeasyMultiple ChoiceObjective-mapped

DP-203 Design and implement data storage Practice Question

You are a data engineer at a financial services company. The company uses Azure Cosmos DB for NoSQL to store customer transaction data. The data is partitioned by customerId. The application team needs to run analytical queries that aggregate transactions by date across all customers. These queries are currently slow and consume high RUs. You need to enable faster analytical queries without impacting the transactional workload. What should you do?

⚠ Common exam trap

Many candidates think increasing RU/s or changing the partition key is a simpler fix, but the DP-203 exam specifically tests the understanding that analytical workloads must be isolated from transactional workloads using a dedicated analytical store like Synapse Link.

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

Enable the Azure Cosmos DB analytical store (Synapse Link) and query the data using Azure Synapse Serverless SQL.

Enabling the Azure Cosmos DB analytical store (Synapse Link) creates a separate column-oriented store optimized for large-scale analytical queries without consuming RUs from the transactional workload. By querying this analytical store using Azure Synapse Serverless SQL, you can run fast aggregations across all customers by date while the transactional container remains unaffected.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increase the provisioned RU/s on the container to handle both transactional and analytical queries.

    Why it's wrong here

    Increasing RU/s does not isolate workloads; analytical queries still compete with transactional.

  • Change the partition key to /date to optimize for analytical queries.

    Why it's wrong here

    Changing partition key would negatively impact transactional queries by customerId.

  • Create a materialized view using the change feed and store aggregated data in a separate container.

    Why it's wrong here

    Materialized views require custom code and still consume transactional RUs for updates.

  • Enable the Azure Cosmos DB analytical store (Synapse Link) and query the data using Azure Synapse Serverless SQL.

    Why this is correct

    Analytical store provides a separate columnar store for efficient analytical queries.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This DP-203 practice question is part of Courseiva's free Microsoft 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 DP-203 exam.