DP-900 Describe core data concepts Practice Question
Which TWO Azure services are primarily used for data integration and orchestration?
⚠ Common exam trap
Candidates often confuse Azure Synapse Analytics (a data warehouse) or Azure Stream Analytics (a real-time processing service) with data integration tools, because they involve data movement or processing, but they are not primarily designed for orchestration and integration.
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
✓
Azure Logic Apps
Azure Logic Apps is correct because it is a serverless workflow service that integrates apps, data, and services using connectors and triggers, making it ideal for data integration and orchestration. Azure Data Factory is correct because it is a cloud-based ETL and data integration service that orchestrates and automates data movement and transformation across various data stores.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Azure Logic Apps
Why this is correct
Azure Logic Apps is a cloud service designed for workflow automation and data integration across disparate systems. It provides prebuilt connectors for hundreds of services and enables you to orchestrate data flows using triggers and actions without writing code. This makes it a first-class tool for integrating data between applications and services, which is why it is a correct answer for this question.
- ✗
Azure Synapse Analytics
Why it's wrong here
Azure Synapse Analytics is an integrated analytics platform that combines big data and data warehousing capabilities. While it can ingest and transform data using pipelines, its primary purpose is to provide analytical querying over large datasets, not to serve as a general-purpose data integration service. Its focus on analytics is what makes it an incorrect choice for a data integration question.
- ✗
Azure Stream Analytics
Why it's wrong here
Azure Stream Analytics is a real-time stream processing engine that analyzes high-volume data in motion from sources like IoT devices, event hubs, and Kafka. It performs computations and transformations on streaming data, but it is specialized for time-series analytics rather than broadly integrating data across different storage and application boundaries. Therefore, it is not considered a primary data integration service.
- ✗
Azure Analysis Services
Why it's wrong here
Azure Analysis Services is a semantic modeling service that provides enterprise-grade tabular data models for business intelligence and reporting. It is used to define measures, relationships, and KPIs, and it consumes data from various sources rather than integrating or transforming it. Its role is analytical and modeling-focused, which is why it is not a data integration service.
- ✓
Azure Data Factory
Why this is correct
Azure Data Factory is a cloud-based ETL and data integration service that allows you to create data-driven workflows for orchestrating data movement and transformation at scale. It supports over 90 connectors, schedules pipelines, and can handle both batch and streaming data, making it a core tool for integrating data across on-premises and cloud sources. This aligns directly with data integration, so it is the correct answer.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
ETL
ETL stands for Extract, Transform, Load, a process that moves data from multiple source systems into a single database, data warehouse, or data lake for analysis and reporting.
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
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Written by Johnson Ajibi, MSc IT Security
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.