01
Data Engineering
Build, transform and process large-scale data using Spark-based tools and lakehouse experiences.
Lakehouse • Notebook • Apache Spark
← Back to DP-700 Learning Path
DP-700Microsoft Fabric Fundamentals
Fabric Workloads
Microsoft Fabric brings different data and analytics capabilities together in one platform. In this lesson, you will understand what a workload is, what each workload is designed for, and how to recognize the right workload in a DP-700 scenario.
⏱ ~15 min•🎓 DP-700 Topic•📚 Beginner Friendly
01 • Start Here
What is a Fabric workload?
A workload is a collection of capabilities targeted to a specific functionality.
Think of a workload as a specialized area of Microsoft Fabric. Each area is designed to help you perform a particular type of data or analytics task.
For DP-700, the important skill is not simply memorizing workload names. You should be able to read a scenario and understand which workload fits the requirement.
Simple way to remember
Requirement→Workload→Fabric capability
Start with the problem you need to solve. Then identify the Fabric workload designed for that type of work.
02 • Watch Before Continuing
What is Microsoft Fabric?
If you are new to Fabric, watch this overview first. It gives you the platform-level picture before we break down individual workloads.
🎥 Yogesh Tech Code • Microsoft Fabric overview
03 • The Fabric Workloads
Know what each workload is designed to do
Microsoft currently documents nine Fabric workloads. Learn them by purpose rather than trying to memorize isolated names.
02
Data Factory
Connect data sources, move data, transform data and orchestrate data workflows.
Pipelines • Copy activity • Dataflow Gen2
03
Data Science
Explore data, build machine learning experiments and develop analytical models.
Notebooks • Experiments • Machine Learning
04
Data Warehouse
Work with structured analytical data using an enterprise data warehouse and T-SQL.
Warehouse • T-SQL • SQL analytics
05
Databases
Use transactional database capabilities within Microsoft Fabric.
SQL database in Fabric • Cosmos DB in Fabric
06
Real-Time Intelligence
Ingest, process and analyze streaming and event data with low latency.
Eventhouse • Eventstream • KQL
07
Power BI
Create semantic models, reports and visual analytics from governed data.
Semantic models • Reports • Dashboards
08
Fabric IQ
Work with business context, semantics and intelligence capabilities across organizational data.
Business semantics • Ontology • Intelligence
09
Industry Solutions
Use industry-focused capabilities and solutions designed around specific business domains.
Industry-focused solutions • Business scenarios
04 • Connect the Concepts
One project can use multiple workloads
Fabric workloads are not isolated islands. A real data solution can use several Fabric experiences for different parts of the same data journey.
01
Ingest
Data Factory
02
Transform
Data Engineering
03
Store
OneLake
04
Analyze
Warehouse / Data Science
05
Present
Power BI
This is a simplified learning model. The exact architecture depends on the business requirement, data sources, processing needs and consumption pattern.
05 • DP-700 Scenario Thinking
Do not memorize. Identify the requirement.
Imagine a company receives customer data every night from several systems. The data must be copied into Fabric, transformed using Spark, analyzed with SQL and finally presented to business users.
Moving and orchestrating data → Data Factory
Spark-based transformation → Data Engineering
SQL-based warehouse analytics → Data Warehouse
Reports and business visualization → Power BI
DP-700 Exam Tip
Read the requirement first. Then identify the workload.
When you see words such as pipeline, orchestration, Spark, T-SQL, streaming, KQL, semantic model or report, use those clues to identify the Fabric experience being described.
06 • Check Your Understanding
What is a Fabric workload?
Select the correct definition.
🚀
Ready to finish this lesson?
Review the workloads, recognize the scenario cues, and mark the lesson as finished to lock your progress.
Previous← Microsoft Fabric ArchitectureNext TopicWorkspaces, Items & Domains →
Phase 1
Microsoft Fabric Fundamentals