What you'll learn

Master Data Integration Techniques
Develop Proficient Data Analytics Skills
Implement and Manage Data Governance
Optimize Data Workflows for Efficiency

Course content

6 sections • 31 lectures • 24h 48m total length

Introduction to Microsoft Fabric || Getting Started with Microsoft Fabric53:34
Hands-On : Create Your First Workspace in Fabric | General Terminology | Roles1:04:56
Hands-On : Create your First Lakehouse | Install OneLake Explorer &Data Studio58:46
Hands-On : Create Your First warehouse in Fabric | | Lakehouse vs Warehouse48:09
Hands-On : Create your First Shortcuts to Lakehouse | Warehouse | Data Lake46:01

Hands-On : Introduction to Data Factory Experience | Pipelines & Dataflows53:05
Discover the data factory experience in Fabric, focusing on pipelines and data flows, comparing Azure and Fabric, and using copy assistant to load lakehouse data.
Hands-On : End-to-End Scenario with Data Factory Pipelines and Dataflows Gen21:08:05
Create an end-to-end fabric workflow: copy blob data into a lake house via a data factory pipeline, then transform with data flow gen2 into bronze and silver tables.
Hands-On : End-to-End Mini Project : Data Factory Pipelines and Dataflows Gen250:43
Hands-On :Copy data from Azure SQL DB to Lakehouse Table | Query | Stored proc41:08
Hands-On :Copy Multiple tables from Azure SQL DB to Lakehouse dynamically46:11
Hands-On : Moving Multiple Folders from Data Lake Storage Gen2 to Lakehouse40:29
Master moving multiple folders from data lake storage gen2 to lakehouse with source cleanup, using copy, get metadata, for each, and warehouse-stored table config to manage dynamic partitions.
Hands-On : Copy data from REST API to Lakehouse in Fabric using Bearer Token31:04

Hands-On : Ingest data from On premise SQL server to Warehouse Incrementally41:00
Hands-On : Copy data from Azure SQL DB to Warehouse using table, query & SP55:29
Learn how to copy data from Azure SQL Database to a warehouse using table, a query, or a stored procedure, then fetch pipeline logs and implement incremental load with pipelines.
Hands-On : Logging Fabric Pipeline Logs to Warehouse table using stored proc52:47
Learn to log fabric pipeline runs to a warehouse table by using a stored procedure that captures run id, execution times, records read/written, and status.
Hands-On Incremental data ingestion from Azure SQL DB to Warehouse in Fabric1:00:29
Hands-On : Microsoft Fabric: Multiple table Incremental data load from Azure SQL1:08:47
20. Hands-On: Filter file using data pipelines in Fabric || Filter Activity47:32

Hands-On: How to run pipeline when dependency job is completed || Event Based41:49
Hands-On :Combining Excel Files from different data providers 2 Unified Table57:34
Hands-On: Copy data from AWS S3 Storage to Lakehouse using Data Pipelines39:29
Hands-On: Multiple tables Dynamic mapping in Copy Activity using config table45:30
Learn to standardize and load multiple azure sql database tables into a warehouse with fabric pipeline, using dynamic mapping, config table with is_active, and for each loop to apply mappings.
Hands-On: Merge Different Excel data of different sheets to unified table41:07

Hands-On: How to handle data pipeline concurrency issue in Microsoft Fabric40:41
Learn how to manage data pipeline concurrency in Microsoft Fabric by using a pipeline process monitor table, run IDs, lookup checks, and conditional script steps to skip overlapping executions.
Hands-On: How to Implement custom pipeline template for reusability |Template46:04
Hands-On: Copy data from On premise SQL Server to Lakehouse using pipelines37:38
Hands-On: Copy data from On premise File System to Lakehouse using pipelines38:05
Copy data from on premise file system to the Lakehouse using a data pipeline in Microsoft Fabric, with a data gateway and get metadata to drive for each folder.
Hands-On: Copy data from snowflake to Lakehouse |Snowflake Free Trail Account39:24
Fabric Summary and Components41:59

Requirements

No coding is required, simple UI based learning, you will learn whatever you need here

Description

"This course offers a comprehensive journey through Microsoft Fabric, guiding you from foundational concepts to advanced techniques. You’ll learn how to integrate diverse data sources, leverage powerful analytics tools, and implement robust data governance practices. Through practical exercises and real-world case studies, you’ll gain hands-on experience to optimize data workflows and apply Microsoft Fabric's capabilities effectively in your projects."
"Dive deep into Microsoft Fabric with this practical course designed to take you from basics to mastery. Explore essential data integration methods, advanced analytics techniques, and effective data governance strategies. Engage with real-world scenarios and hands-on exercises to enhance your skills and optimize data workflows, preparing you to leverage Microsoft Fabric’s full potential in your data management and analytics tasks."
"Master Microsoft Fabric with our in-depth course that covers everything from foundational principles to advanced applications. This guide will teach you how to seamlessly integrate data, perform advanced analytics, and manage data governance within Microsoft Fabric. Through practical exercises and real-life case studies, you will develop the skills needed to design efficient data workflows and apply Microsoft Fabric's tools to solve complex data challenges."
"This course provides a practical and thorough exploration of Microsoft Fabric, moving from fundamental concepts to advanced mastery. You will learn how to integrate various data sources, utilize analytics tools for actionable insights, and enforce effective data governance. Hands-on practice and real-world examples will equip you with the skills to optimize data workflows and apply Microsoft Fabric's features to enhance your data management and analytics capabilities."

Who this course is for:

Data Engineers, Data Architects, Data Science and Data Analyst,Anybody who wants to become Data Architect

What you'll learn

Explore related topics

Course content

Introduction5 lectures • 4hr 31min

Development of Data Pipeline and Dataflow Gen27 lectures • 5hr 31min

Data Pipelines which ingest data from On Premise to Cloud2 lectures • 1hr 31min

Incremental data pipelines and pipeline logging and scheduling6 lectures • 5hr 26min

Advanced pipelines like dependency pipelines and dynamic schema and cross cloud5 lectures • 3hr 45min

Pipeline concurrency and Pipeline templates development6 lectures • 4hr 4min

Requirements

Description

Who this course is for: