DP-700 Microsoft Fabric Data Engineer Training Course
DP-700T00 Microsoft Fabric Analytics Engineer Certification
Turn big data into business insights and learn to build super-fast data systems, handle huge amounts of information and make charts.
The DP-700 course covers configuring Spark workspace settings, domain workspace settings, OneLake workspace settings, data workflow workspace settings, version control, implementing database projects, creating and onfiguring deployment pipelines, workspace-level access controls, item-level access controls, row-level, column-level, object-level, and folder/file-level access controls, dynamic data masking, appyling sensitivity labels to items and endorsing items and more.
This course is available in Melbourne, Sydney, Brisbane, Adelaide, Canberra, Perth, Hobart and throughout Australia Live Virtually.
- Basic experience with data, SQL for querying, and data movement/transformation
- Familiarity with cloud platforms (like Azure) and basic programming in Python or R
Candidates can achieve this certification by passing the following exam(s).
- DP-700 Microsoft Fabric Data Engineer
The certification exam can be registered and attempted within 3 months of course/module completion at our training centre on weekdays during normal business hours (excludes public holidays)
DP-700 Microsoft Fabric Data Engineer material provided
- Configure Microsoft Fabric workspace settings
- Implement lifecycle management in Fabric
- Configure security and governance
- Orchestrate processes
- Design and implement loading patterns
- Ingest and transform batch data
- Ingest and transform streaming data
- Monitor Fabric items
- Identify and resolve errors
- Optimise performance
- Data professionals with experience in data extraction, transformation, and loading (ETL).
- Professionals who need to create and deploy data engineering solutions using Microsoft Fabric for enterprise-scale analytics.
- Learners with experience manipulating and transforming data using SQL, PySpark, or Kusto Query Language (KQL).
- Configure Spark workspace settings
- Configure domain workspace settings
- Configure OneLake workspace settings
- Configure data workflow workspace settings
- Configure version control
- Implement database projects
- Create and configure deployment pipelines
- Implement workspace-level access controls
- Implement item-level access controls
- Implement row-level, column-level, object-level, and folder/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
- 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 data transformation
- Create and manage shortcuts to data
- Implement mirroring
- Ingest data by using pipelines
- Transform data by 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 by using eventstreams
- Process data by using Spark structured streaming
- Process data by using KQL
- Create windowing functions
- 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
- AZ‑900: Microsoft Azure Fundamentals
- MS‑900: Microsoft 365 Fundamentals
- MS‑102: Microsoft 365 Administrator
- AZ‑305: Designing Microsoft Azure Infrastructure Solutions
- SC‑900: Microsoft Security, Compliance, and Identity Fundamentals
- SC‑100: Microsoft Cybersecurity Architect
- SC‑400: Microsoft Information Protection Administrator
- MS‑720T00: Microsoft Teams Voice Engineer
- AI‑900: Microsoft Azure AI Fundamentals
- DA‑100: Analyzing Data with Power BI
- AZ‑104: Microsoft Azure Administrator
- AZ‑400: Designing and Implementing Microsoft DevOps Solutions
- DP‑203: Data Engineering on Microsoft Azure
- PL‑300: Microsoft Power Platform Solution Architect
- MB‑300: Microsoft Dynamics 365: Core Finance and Operations
Take the Certification Exam within 3 months of course / module completion
Take the official certification exam at Logitrain, a local VUE test centre or online
Course material in digital format is included for flexibility and ease of use
Practise questions are provided for better understanding of the key concepts
Attend the course with an instructor at our training centre or from anywhere
Relax, we will beat competitor’s advertised price. Our course has no extra costs
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The supply of this course/package/program is governed by our terms and conditions. Please read them carefully before enrolling, as enrolment is conditional on acceptance of these terms and conditions. Proposed course dates are given, course runs subject to availability and minimum registrations.
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