DP-900 Describe an analytics workload on Azure Practice Question
A small business wants to start using Azure for analytics. They have a few CSV files stored on-premises that they want to analyze. They have no budget for complex infrastructure and prefer a fully managed, serverless solution. They need to create interactive visualizations and share them with their team. The data does not change frequently, so they are okay with daily refreshes. Which of the following options should they choose? A) Upload the CSV files to Azure Data Lake Storage Gen2, use Azure Databricks to create a data processing pipeline, and then use Power BI to visualize the results. B) Upload the CSV files to Azure Blob Storage, use Azure Data Factory to load the data into Azure SQL Database, and then use Power BI to connect and visualize. C) Upload the CSV files to OneDrive for Business, use Power BI Desktop to import the data, and publish to Power BI Service with scheduled refresh. D) Upload the CSV files to Azure Data Lake Storage Gen2, use Azure Synapse Serverless SQL pool to query the data, and then use Power BI to connect. Which option is the simplest and most cost-effective?
⚠ Common exam trap
The trap here is that candidates often overcomplicate the solution by choosing Azure-specific storage and compute services (like Data Lake, Databricks, or Synapse) when a simpler, fully managed tool like Power BI with OneDrive is sufficient and more cost-effective for small-scale, static data analytics.
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
✓
Option C
It uses OneDrive for Business as a simple storage location, Power BI Desktop for importing CSV data, and Power BI Service for publishing and sharing interactive visualizations with scheduled daily refresh. This is fully managed, serverless, and requires no complex infrastructure, aligning perfectly with the small business's budget and simplicity requirements.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Option B
Why it's wrong here
Option B is wrong because it pulls in multiple Azure services that are unnecessary for this scenario. Azure Data Factory adds a data orchestration layer, and Azure SQL Database requires provisioning a server with ongoing compute and storage costs. Together they increase both financial cost and operational complexity compared to simply loading data into Power BI for analysis.
- ✗
Option D
Why it's wrong here
Option D is wrong because Azure Synapse serverless, although cost-efficient for occasional large queries, assumes a lakehouse architecture with external tables, file formats, and T-SQL skills. A small business would need to build a data lake and define schemas before analyzing anything, which is far more configuration than the minimal, low-code analytics experience the question calls for.
- ✓
Option C
Why this is correct
Option C is correct because it delivers a complete analytics workflow using Power BI Desktop and OneDrive with no Azure compute or storage services to provision. Data can be modeled in a desktop file, published to the Power BI service, and refreshed from OneDrive or other connected sources, making it the simplest and lowest-cost way to begin cloud-based analytics without operational overhead.
- ✗
Option A
Why it's wrong here
Option A is wrong because Azure Databricks is a managed Spark platform intended for large-scale data engineering, machine learning, and streaming workloads. It requires creating a workspace, configuring clusters, and maintaining notebooks, all of which demand specialized skills and incur per-hour cluster costs. Combining it with Azure Data Lake Storage compounds the overengineering for a small business that simply wants descriptive analytics and shared reports.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Azure SQL Database
Azure SQL Database is a fully managed relational database-as-a-service (DBaaS) in Microsoft Azure, based on the SQL Server engine, that handles scaling, backups, patching, and high availability automatically.
Key term
Serverless SQL pool
Serverless SQL pool is an on-demand, pay-per-query analytics service in Azure that lets you query data stored in data lakes without provisioning or managing any dedicated infrastructure.
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Senior Network & Security Engineer · founder of Courseiva
This DP-900 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-900 exam.