Intermediate Level

Micrsoft Certified Fabric Data Engineer Associate (DP-700

★ 4.8 (300 learners) 60 hrs total 1 modules

Microsoft Azure Azure DevOps Entra ID Power BI Delta Lake Apache Spark +3 more

Only 5 seats left · Next batch starts 15 Aug 2026

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60 hrs: of content
1 modules: in curriculum
16 projects: hands-on builds
Intermediate: difficulty

Curriculum covers

Frameworks you'll master

9 tools & frameworks

Microsoft Azure Azure DevOps Entra ID Power BI Delta Lake Apache Spark PySpark Azure Data Factory Microsoft Fabric

Course Curriculum

1 modules · 60 hours · 24 live sessions

Microsoft DP700: Fabric Data Engineer Associate 24 sessions

Understanding Microsoft Fabric
Section Introduction
Evolution of Data Architectures
Delta Lake Structure
Why Microsoft Fabric is needed
Microsoft's definition of Fabric
How to enable and access Microsoft Fabric
Fabric License and costing
Update in Fabric UI
Experiences in Microsoft Fabric
Update to Fabric UI Experiences as Workloads
Fabric Terminology
One Lake in Fabric
One copy for all Computes in Microsoft Fabric
Microsoft Fabric Fundamentals
Why Microsoft Fabric?
What is Microsoft Fabric?
Hierarchy in Microsoft Fabric
Roles in Microsoft Fabric
Fabric Free Account
Fabric Portal Overview
Microsoft OneLake – Storage Solution for Microsoft Fabric
What is OneLake
Why OneLake?
Manage your data One Lake File Explorer
Fabric Lakehouse – Store Structured, Semi Structured and Unstructured Data
What is a Fabric Lakehouse?
Create your first Lakehouse
Load data to Lakehouse
OneLake file explorer with Lakehouse
Create tables in Lakehouse
Parquet files with Lakehouse
Shortcuts in Fabric
What are Internal Shortcuts?
What are External Shortcuts?
Internal Shortcuts with Files
Internal Shortcuts with Tables
External Shortcuts Illustrations
Caching in Shortcuts
Lakehouse with Schema (NEW)
Lakehouse SQL Endpoints
Fabric Lakehouse
Understanding Fabric Workspaces
Update in the UI of Fabric
Enable Fabric Trail and Create workspace
Purchasing Fabric Capacity from Azure
Workspace roles in Microsoft Fabric
Update in the create items UI
Creating a Lakehouse
What is inside Lakehouse
Uploading data to Lakehouse
Uploading Folder into Lakehouse
SQL analytics endpoint in Lakehouse
Access SQL analytics endpoint using SSMS
Visual Query in SQL endpoint
Default Semantic Model
One Lake File Explorer
Fabric Data Factory
Fabric Data Factory UI
Ways to load data into Lakehouse
Fabric Data Factory vs Azure Data Factory Scenario
Gateway types in Microsoft Fabric
Installing Onprem data gateway
Create Connection to SQL Server
Pipeline to ingest OnPrem SQL data to Lakehouse
Scenario completed using Fabric data factory
Dataflow Gen2 – Intro
Creating Dataflow Gen2
Dataflow Gen2 in Fabric vs Dataflows in ADF
Fabric Data Factory – Design and Build EndToEnd ETL Pipelines and Workflows
Data Ingestion in Fabric
What is Fabric Data Factory
Fabric Data Factory Overview
Copy Activity in Fabric Data Factory
Ingest data from Azure Data Lake Storage Gen 2
Loops and Parameters in Fabric Data Factory
Metadata Activity
Filter Activity
Conditional Activity If Condition
Deletion in Data Factory
Variables in Fabric Data Factory
How to send email notification on failure?
Parent and Child Pipelines
Triggers in Fabric Data Factory
Monitoring in Fabric Data Factory
Transform our Data with Low/NoCode with Dataflow Gen 2
Dataflow Gen2 overview
Type casting in DataflowGen2
Replace Values in DataflowGen2
String Transformations
Apply statistical functions
Diagram view in DataflowGen2
Apply Joins in DataflowGen2
Adding a destination (Lakehouse
Scheduling Dataflows
Integrating DataflowGen2 with Data Factory
Fabric OneLake
Loading data status
Shortcuts in Fabric Intro
Prerequisites to Create a shortcut
Creating a shortcut in Files of Lakehouse
Criteria to create shortcuts in table section
Uploading required files and access for synapse
Right way to create a shortcut in table's section
Creating delta file
Creating shortcut in Table's section
Scenario Creating shortcut with delta in a subfolder
Scenario Creating shortcut with only parquet format
Requirements to create shortcuts in Table and files section
Updation Scenario 1 Lakehouse to Datalake
Updation Scenario 2 Datalake to Lakehouse
Shortcut deletion scenarios intro
Deletion Scenario 1 Delete in Lakehouse files
Deletion Scenario 2 Delete in ADLS
Deletion Scenario 3 Delete table data in Lakehouse
Deletion Scenario 4 Delete table data in ADLS
Deletion Scenario 5 Deleting entire shortcut
Shortcut deleting scenario summary
Spark Development – The Heart of Fabric Data Engineering
First of all Understand SPARK
Nodes Sizes in Fabric
Starter Pools VS Custom Pools
Fabric Notebooks Overview
PySpark Fundamentals
Type Casting in PySpark
Transform Date Columns
Replacing Values in PySpark
PySpark Intermediate Level Functions
Transform time sensitive columns with Timestamp Functions
Spark SQL Run SQL queries in PySpark
Data Visualization for big data analysis
External vs Managed Tables
NotebookUtils in PySpark (MSSparkUtils)
Delta Lake Tables
Time Travel in Delta Lake Tables
OPTIMIZATION strategies in delta lake tables
VACUUM and Optimize Write Command
Spark Streaming with Delta Tables
Isolated Environments in Fabric Spark
How to create Environments in Fabric
Monitoring and Scheduling Spark Notebooks
Spark Job Definition
How to Import Notebooks from PC
Fabric Synapse Data Engineering
Ingestion to Lakehouse status
Spark in Microsoft Fabric
Spark pools in Microsoft Fabric
Spark pool node size
Customizing Starter pools
Creating a custom pool in Workspace
Standard vs High Concurrency Sessions
Changing Spark Settings to Starter Pool
Update in attaching Lakehouse to Notebook Option
Understanding Notebooks UI
Fabric Notebook basics
MSSparkUtils Intro
MSSparkUtils FS Mount
MSSparkUtils FS Other utils
MSSparkUtils FS FastCp
Creating Folders in Microsoft Fabric
MSSparkUtils Notebook Utils Run exit
MSSparkUtils Notebook RunMultiple
Access ADLS data to Lakehouse Intro
Access ADLS using Entra ID
Access ADLS using Service principal
Access ADLS using SP with keyvault
Call Fabric notebook from Fabric pipeline
Managed vs External table Intro
Create a Managed Table
Create an External Table
Shortcut Table is an external or managed table
Data Wrangler in Fabric Notebook
Environments in Microsoft Fabric
Understanding Vorder optimization
Inspire us with your Thoughts
Spark Job Definition
What is a data mesh
Creating domains in Fabric
Fabric Data Warehouse – A Lake Centric Data Warehouse for our GOLD Layer
Data Warehouse Fundamentals
Fabric Data Warehouse Overview
Load data to Data Warehouse
COPY INTO command in Fabric Data Warehouse
CTAS Copy Table As Select
Gold Layer Aggregated View using TSQL
Gold Layer Business View using TSQL
TSQL Functions
TSQL Stored Procedures
Dynamic Management Views
Query Insights Views
Visual Query Editor in Fabric Data Warehouse
Integrating TSQL with Notebook
SSMS Setup
Access Control in Fabric Data Warehouse
Dynamic Data Masking
Column Level Security
Row Level Security
Semantic Models
Direct Lake in Fabric
Synapse Migration to Microsoft Fabric
Manual import from Synapse to Fabric
Automated way to import and export notebooks Intro
Migrate all notebooks from Synapse to fabric
Possibility of Migration of Pipelines to Fabric pipelines
Ways to migrate ADLS data to Fabric OneLake
Migrate ADLS data to OneLake using Storage Explorer
Fabric Capacity Metrics App
Install Capacity Metrics App
Understanding UI of Capacity Metrics App
Capacity Units consumption
Throttling vs Smoothing
Throttling stage Overage Protection Policy
Other throttling stages
Throttling stages Summary
Overages in Fabric
System Events in Fabric
Matrix Visual
Fabric Synapse Data Warehouse
Creating a Warehouse in Fabric
Warehouse vs SQL Analytics Endpoint
Creating a table and Limitations
Ways to Load Data into Warehouse
Loading Data using COPY INTO Command
Loading Data using Pipeline to Warehouse
Loading Data using Dataflow Gen2
Data Sharing Lakehouse & Warehouse
Cross Database Ingestion in Warehouse
Lakehouse vs Warehouse when to choose what
Different Medallion Architectural patterns
Update Lakehouse data from WH and vice versa
SQL query as session in Fabric
Zero Copy clone within and across Schema
Time Travel in Warehouse
Benefits & Limitations of Zero Copy clones
Cloning single or multiple tables using UI
Query Insights in Warehouse
Fabric Data Governance
Why Fabric Access Control
Workspace Level Access Control
Item Level Access Control
One Lake Level Access Control
Data Lineage
Endorsements
Monitoring in Fabric
Fabric Admin Access
Fabric Connections and Gateways
Fabric Capacity Metric App
Fabric Access Control and Permissions
Microsoft Fabric Structure
Tenant Level permissions
Capacity Level Permissions
Creating new user in Entra ID
Workspace roles Workspace Administration
Workspace roles Data pipeline permissions
Workspace Roles Notebook, Spark jobs, etc
Data Warehouse permissions Intro
Workspace Roles Accessing shortcuts internal to fabric Theory
Workspace Roles Accessing Shortcuts Internal to Fabric Practical
Workspace Roles Accessing ADLS shortcuts Theory
Workspace Roles Accessing ADLS shortcuts Practical
Workspace Roles Lakehouse permission
Item level permissions Intro
Warehouse Sharing No additional permissions
Warehouse Sharing Read Data permissions
Warehouse Sharing Read All permissions
Warehouse Sharing Build permissions
Extend Microsoft Fabric Trail
Lakehouse Sharing All permissions
Notebook Item Sharing
Manage OneLake data access
RowLevel Security in Warehouse and SQL endpoint
Dynamic Data Masking in Warehouse and SQL endpoint
Column & Object level security in Warehouse and SQL endpoint
Real Time Analytics – Eventstream, Eventhouse, KSQL DB (RealTime Analytics in Microsoft Fabric)
What is Real Time Analytics?
Tumbling Windows
Hopping Windows
Sliding Windows
Session Windows
Snapshot Windows
Eventstream in Fabric
Transforming Real Time Data
Eventhouse and KQL DB
Kusto Query Language Overview
KQL Basics
Filtering and Date Functions
Aggregation Functions in KQL
Materialized Views in KQL
Functions in KQL
Real Time Dashboards
Base Queries for Real Time Dashboards
Fabric Activator
Microsoft Power BI in Fabric (Direct Lake & Power BI)
Default Semantic Model Intro
Manage default Semantic Model
Accessing Lakehouse or Warehouse using Power BI Desktop
Automatically update semantic model in Lakehouse or warehouse
Creating new Semantic Model
Lineage view and Impact Analysis
Connect using XMLA endpoint and read write using Tabular Editor
What is a Direct Lake
Direct Lake Practical
Direct Lake vs Direct Query vs Import modes
Refresh a Semantic Model Manual
Refresh Semantic model from Notebook
Refresh Semantic Model from XMLA Endpoint
Refresh Semantic Model from Data Pipeline
Fallback to Direct Query Scenarios
Handling Fallback behavior of Semantic Models
Copy Multiple measures from One Model to another in Fabric.mp4
Rowlevel security in Power BI
Rowlevel security without Viewer Role
Build permission to user with RLS
Dynamic Rowlevel Security
Object level Security with viewer role
Object level security without Viewer role
Column level security
Data Science in Microsoft Fabric
Data Science in Microsoft Fabric
Notebooks
Experiments
Models
Preparing Data Data Wrangling
EndtoEnd Project: Getting Set Up
EndtoEnd Project: Ingesting Data
EndtoEnd Project: Exploring the Data Part 1
EndtoEnd Project: Exploring the Data Part 2
EndtoEnd Project: Exploring the Data Part 3
EndtoEnd Project: Exploring the Data Part 4
EndtoEnd Project: Train and Evaluate the Data Part 1
EndtoEnd Project: Train and Evaluate the Data Part 2
EndtoEnd Project: Train and Evaluate the Data Part 3
EndtoEnd Project: Train and Evaluate the Data Part 4
EndtoEnd Project: Reporting Part 1
EndtoEnd Project: Reporting Part 2
Fabric End to End Project
Different Medallion architectures in Fabric
Understanding domain and dataset information
Project Architecture
Creating workspace for project and review dataset
Get data from Raw to landing theory
Raw to landing zone
Different incremental loading patterns
Incrementally ingest from Raw to landing zone
Automate ingest from Raw to Landing using pipeline
Ingest data from Landing to Bronze layer Theory
Understanding UPSERT logic for Landing to Bronze ingestion
Landing to Bronze layer practical
Reading landing to bronze from next partition
UPSERT scenario practical Landing to bronze
Bronze layer to silver layer Theory
Understanding data transformations and UPSERT logic for silver table
Silver table Data cleaning
Silver Layer data transformations
Gold Layer Facts and dimensions table Theory
Gold Layer Facts and dimension tables Practical
Data modelling and creating a report
Orchestrate end to end pipeline and execute it
Fabric Git Integration
Creating data sources for PROD
Changes made to support Git integration
Executing to check if changes were working
Sign up with Azure DevOps account
Connect Fabric workspace to Azure DevOps
Git integration permissions and Limitations
Locking main branch with branch policy
Understanding Continuous Integration (CI) in Fabric
Continuous Integration in Fabric Workspace
Status of workspace created for feature branch
Understanding Continuous Deployment in Fabric
Deploying Fabric items from Dev to Prod
Deployment rules to Change data sources of Prod workspace
End to End execution in PROD
Git integration for Power BI developers
Summary of version control for Power BI
Fabric Data Agent
What is Fabric Data Agent
How Fabric Data Agent works
Prerequisites for Data Agent
Associate Fabric Capacity to Workspace
Create and configure Fabric Data Agent
Fabric Data Agent sharing
ECommerce Project – ADLS + Data Pipelines + PySpark + Power BI
PROJECT INTRODUCTION
PROJECT SETUP & SOURCE SETUP
FABRIC WORKSPACE & LAKEHOUSE
DATA PIPELINE ADLS TO LAKEHOUSE COPY
DATA CLEANING & REPORTING PYSPARK + POWER BI
MEDALLION ARCHITECTURE : END TO END PROJECTS
PROJECT INTRODUCTION
DATA PIPELIENE ADLS TO LAKEHOUSE
DATA CLEANING & REPORTING PYSPARK & POWER BI
DATA MIGRATION PROJECT: END TO END DATA PIPELINE
PROJECT INTRODUCTION
BUSINESS USE CASE & PROBLE
PRACTICAL END TO END DATA PIPELINE
ECommerce Order Analytics Project – Spark SQL + DATA PIPELINE + Power BI
PROJECT INTRODUCTION
PROJECT PRACTICAL DATA PIPELINE + LAKEHOUSE + SPARK SQL
POWER BI & REPORTING
HR ANALYTIC Project – DATA FLOW GEN2 + DATA PIPELINE + Power BI
PROJECT INTRODUCTION & BUSINESS USE CASE
PROJECT PRACTICAL DATA PIPELIEN + LAKEHOUSE + DATA FLOW GEN2 + POWER BI
INCREMENTAL DATA LOAD – END TO END PIPELINE
PROJECT INTRODUCTION & BUSINESS USE CASE
END TO END DATA PIPELINE
INSURANCE PROJECTS – DATA PIPELINE + LAKEHOUSE + PYSPARK + REPORTING
PROJECT INTRODUCTION & BUSINESS USECASE
PROJECT PRACTICAL ADLS + LAKEHOUSE+ PYSPARK + REPORTING
RETAIL DATA ENGINEERING PROJECTS
PROJECT INTRODUCTION
PROJECTS PRACTICAL DATA PIPELINE + PYSPARK + LAKEHOUSE + REPORTING
SCD TYPE 1 DATA PIPELINE PROJECT
PROJECT INTRODUCTION
PROJECTS PRACTICAL DATA PIPELINE + PYSPARK + LAKEHOUSE + REPORTING
SCD TYPE 2 DATA PIPELINE PROJECT
PROJECT INTRODUCTION
DATASET UNDERSTANDING – SCD TYPE2

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Batch Schedule

⚡ Seats filling fast — only 5 remaining across all batches

Available Batches
Batch Type	Schedule	Duration	Next Start Date	Availability
Weekend	Sat & Sun, 10am–1pm	10 weeks	15 Aug 2026	Only 5 seats left
Weekday	Mon–Fri, 7–9pm	8 weeks	17 Aug 2026	Available
Fast-track	Mon–Sun, 6 hours/day	2 weeks	24 Aug 2026	Available

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