Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
23 Hour(s) 17 Minute(s)
Language
English
Taught by
Ansh Lamba JSR
Rating
1 views
Course Overview
(2026 NEW) Pass the Fabric Data Engineer Associate Certification DP-700 | PySpark, T-SQL, KQL, M
Are you ready to become a Microsoft Certified Fabric Data Engineer Associate (DP-700) with the LATEST 2026 syllabus?
Whether you're a complete beginner or a working professional looking to level up, this course will walk you through everything you need to know — with a hands-on, engaging, and practical approach.
This course is designed to help YOU PASS the DP-700 exam and MASTER the Fabric platform with confidence.
GAIN STRONG HANDS-ON WITH :
- OneLake & Shortcuts - Learn how to access data instantly across domains with OneLake’s game-changing shortcuts.
- Fabric Data Factory - Build real-time, end-to-end pipelines with powerful visual tools and dataflows.
- Lakehouse Architecture - Discover how to combine data engineering and analytics in one powerful environment.
- PySpark Development in Notebooks - Use Notebookutils, environment configs, and PySpark magic to build real projects inside Microsoft Fabric
- Data Warehouse + T-SQL Mastery - Write complex stored procedures, functions, and T-SQL queries like a pro — with tips, tricks, and real examples.
- Real-Time Analytics with KQL - Master Kusto Query Language (KQL) to build blazing-fast real-time dashboards using Eventstream, Eventhouse, and KQL DB.
- CI/CD for Fabric Projects - Automate deployments using Azure DevOps + Fabric Pipelines.
- Data Governance Simplified - Understand lineage, endorsements, sensitivity labels and more.
- M Language - Build ETL solutions using Power Query M code
- Materialized Lake Views - Build modern PySpark workflows using the latest MLV framework.
What Makes This Course Different?
Super Engaging Lectures – No boring theory! Concepts are explained in a fun, clear, and beginner-friendly way with real-life analogies and visuals.
Deep Dive into Every Topic – We don’t just scratch the surface. You'll understand the “why” and “how” behind every feature so you can apply it in real projects and interviews.
Strong Hands-On Focus – Learn by doing! From pipelines to notebooks to dashboards, you’ll build real solutions step-by-step, just like a Fabric Data Engineer does.
Course Content
- 16 section(s)
- 199 lecture(s)
- Section 1 Introduction
- Section 2 Resources
- Section 3 Microsoft Fabric Fundamentals
- Section 4 Microsoft OneLake
- Section 5 Fabric Lakehouse
- Section 6 Fabric Data Factory
- Section 7 Dataflow Gen 2
- Section 8 PySpark Development
- Section 9 Data Warehouse & Security
- Section 10 Fabric Data Governance
- Section 11 Real Time Analytics with EventStream, EventHouse, KQL DB
- Section 12 CI/CD with Azure DevOps and Deployment Pipelines
- Section 13 M Language (Power Query)
- Section 14 OPTIMIZATION
- Section 15 Spark Structured Streaming
- Section 16 Materialized Lake Views (MLV)
What You’ll Learn
- [2026 UPDATED] Become a Microsoft Fabric Data Engineer with the LATEST upgrades, Learn Microsoft Fabric fundamentals, including the Medallion Architecture and Delta Lake., Get hands-on with OneLake and learn how internal and external shortcuts work behind the scenes., Build complete end-to-end ETL pipelines using Fabric Data Factory with real-world examples., Clean, transform, and enrich data using Data Flow Gen2—no code or low code., Master the Lakehouse architecture and understand how it bridges the gap between data lakes and data warehouses., Learn PySpark development in Fabric, including the latest features like environments and notebooks., Explore powerful data warehousing capabilities and write advanced T-SQL queries, functions, and stored procedures., Ingest, transform, and load real-time data using Eventstreams, Eventhouse, and KQL DB. Get confident with the Kusto Query Language., Implement CI/CD using Azure DevOps and Fabric deployment pipelines for faster and safer delivery., Secure and manage your analytics solutions using Fabric’s data governance tools like lineage tracking, endorsements, and workspace roles, Monitor and optimize your analytics solutions using Monitor Hub and Spark Web UI, Write efficient M-Language code to build ETL solutions using Power Query, Learn recently added Materialized Lake Views (MLVs) framework for automated data engineering pipelines.
Skills covered in this course
Reviews
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PPrathik Bafna
Good content, but the trainer adds a lot of unnecessary talk.
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AAmit Sethi
lacks concrete examples or real-time scenarios & contains many repetitive comments that can actually reduce tutorial length of 17 hrs to half
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MMd Mohiuddin
It is really, good but it should include mock exam questions at the end to check understanding.
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VVinay Arya
liked the course with detailed and easy explanations , covered all the things with good pace. hope to learn many more from the instructor in future.
