DP-700 Microsoft Fabric Data Engineer Training Course

The Microsoft Certified: Fabric Data Engineer Associate credential proves you can design, build and run data engineering solutions on Microsoft Fabric, the platform organisations are standardising their analytics on. It sits at the engineering end of the Fabric path, alongside the analytics focused DP-600 Microsoft Fabric Analytics Engineer course, and it is the current successor to the retired DP-203 Azure Data Engineer, so it is where employer demand is heading.

Choosing Logitrain means the official exam fee is included and you keep the digital course material. Every course is backed by our price beat guarantee, so there are no hidden costs. You can sit the exam at the Logitrain Pearson VUE test centre, at another Pearson VUE centre, or online through Pearson VUE online proctoring, and you can train in Melbourne, Sydney and Brisbane or live online anywhere in Australia.

There are no formal prerequisites for the DP-700 course. Microsoft recommends you are comfortable working with data and can manipulate and transform it using one of SQL, PySpark or Kusto Query Language (KQL), along with a basic understanding of core data concepts and cloud services such as Azure.

If you are new to cloud data, start with the DP-900 Microsoft Azure Data Fundamentals course to build that base before enrolling.

Candidates can achieve this certification by passing the following exam.

• DP-700 Implement Data Engineering Solutions Using Microsoft Fabric, leading to Microsoft Certified: Fabric Data Engineer Associate

You can book and sit the exam within three months of finishing your course. Sit it at the Logitrain Pearson VUE test centre, at any other Pearson VUE test centre, or online through Pearson VUE online proctoring from a private space.

Exam format: the exam runs for 100 minutes and is scored on a scale of 100 to 1000, with 700 required to pass. It is proctored and may include interactive components and case studies.

The DP-700 Microsoft Fabric Data Engineer digital course material is included, mapped to the current exam and yours to keep for reference after the course.

• Configure Microsoft Fabric workspace, domain and OneLake settings
• Implement lifecycle management, version control and deployment pipelines
• Secure workspaces with workspace, item, row, column and object level access controls
• Apply sensitivity labels, dynamic data masking and workspace logging
• Orchestrate processes using pipelines and notebooks with parameters and triggers
• Design and implement full and incremental data loading patterns
• Ingest batch data using pipelines, dataflows and shortcuts
• Ingest and process streaming data with eventstreams, Spark structured streaming and KQL
• Transform data using PySpark, SQL and KQL
• Handle duplicate, missing and late arriving data
• Build a dimensional model and prepare data for loading
• Implement mirroring and choose appropriate data stores
• Monitor data ingestion, transformation and semantic model refresh
• Configure alerts and resolve pipeline, dataflow, notebook and eventhouse errors
• Optimise lakehouse tables, warehouses, pipelines, Spark and query performance

• Data engineers building and managing analytics solutions
• ETL and data integration developers moving to Microsoft Fabric
• Database administrators and SQL developers expanding into data engineering
• Data analysts and BI developers who want engineering skills
• Data architects who design data engineering solutions
• Analytics and data platform professionals adopting Fabric
• Career changers with SQL, PySpark or KQL experience moving into data engineering
• Professionals preparing for the Microsoft Certified: Fabric Data Engineer Associate certification

Implement and manage an analytics solution

• Configure Spark, domain, OneLake and data workflow workspace settings
• Configure version control and implement database projects
• Create and configure deployment pipelines
• Implement workspace level and item level access controls
• Implement row, column, object and file level access controls
• Implement dynamic data masking
• Apply sensitivity labels to items
• Endorse items
• Implement and use workspace logging
• Choose between a pipeline and a notebook
• Design and implement schedules and event based triggers
• Implement orchestration patterns with notebooks and pipelines, including parameters and dynamic expressions

Ingest and transform data

• Design and implement full and incremental data loads
• Prepare data for loading into a dimensional model
• Design and implement a loading pattern for streaming data
• Choose an appropriate data store
• Choose between dataflows, notebooks, KQL and T-SQL for transformation
• Create and manage shortcuts to data
• Implement mirroring
• Ingest data using pipelines
• Transform data using PySpark, SQL and KQL
• Denormalise data
• Group and aggregate data
• Handle duplicate, missing and late arriving data
• Choose an appropriate streaming engine
• Choose between native storage, mirrored storage or shortcuts in Real-Time Intelligence
• Process data using eventstreams
• Process data using Spark structured streaming
• Process data using KQL
• Create windowing functions

Monitor and optimise an analytics solution

• Monitor data ingestion
• Monitor data transformation
• Monitor semantic model refresh
• Configure alerts
• Identify and resolve pipeline errors
• Identify and resolve dataflow errors
• Identify and resolve notebook errors
• Identify and resolve eventhouse errors
• Identify and resolve eventstream errors
• Identify and resolve T-SQL errors
• Optimise a lakehouse table
• Optimise a pipeline
• Optimise a data warehouse
• Optimise eventstreams and eventhouses
• Optimise Spark performance
• Optimise query performance

• DP-900 Microsoft Azure Data Fundamentals is the entry point and the best starting course if you are new to cloud data.
• DP-600 Microsoft Fabric Analytics Engineer is the companion Fabric credential covering the analytics and Power BI side, and many professionals hold both.
• PL-300 Microsoft Power BI Data Analyst builds reporting and semantic model skills that pair well with Fabric engineering.
• AZ-900 Microsoft Azure Fundamentals gives a broad cloud grounding for anyone newer to Azure.
• Data Analytics Job Ready Program combines training, certification, internship and career counselling for those targeting a data role.
• Microsoft Azure courses lists the full range of Azure and data courses in this category.

Got a team to train? Logitrain can deliver the DP-700 Microsoft Fabric Data Engineer course in house at your premises anywhere in Australia, with the same skilled trainer, digital course material, practice questions and included official exam as the public courses. It suits teams who want everyone trained together on dates that suit the business.

What is the DP-700 certification?

It is the Microsoft Certified: Fabric Data Engineer Associate credential. It shows you can build, secure, monitor and optimise data engineering solutions on Microsoft Fabric, working with lakehouses, warehouses, pipelines, notebooks and real-time data.

Is the exam included in the DP-700 course?

Yes. The official exam is included, and you can book and sit it within three months of finishing your course. You can sit it at the Logitrain Pearson VUE test centre, at another Pearson VUE centre, or online through Pearson VUE online proctoring.

Do I need any prerequisites for DP-700?

There are no formal prerequisites. It helps to be comfortable manipulating data with SQL, PySpark or KQL and to understand core data concepts. If you are new to cloud data, start with the DP-900 Microsoft Azure Data Fundamentals course first.

Is DP-700 the current Microsoft Fabric Data Engineer certification?

Yes. DP-700 is the current data engineering credential and the successor to the retired DP-203 Azure Data Engineer, reflecting the move to the unified Microsoft Fabric platform.

How long is the DP-700 course?

The course runs for 4 days full-time on weekdays, or 4 weeks part-time, where each full-time day maps to one part-time week so you can study around work.

Where can I do the DP-700 course?

In person in Melbourne, Sydney, Brisbane, Adelaide, Perth and Canberra, plus live online across Australia, all delivered live in real time with a trainer.

Should I do DP-700 or DP-600 first?

It depends on your role. If your focus is data engineering, pipelines and loading patterns, start with DP-700. If your focus is analytics, semantic models and Power BI, start with DP-600. They are companions, so many people complete both, and anyone new to cloud data should begin with DP-900.