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Batch Date: July 22nd @6:00AM

Faculty: Mr. N. Vijay Sunder Sagar (20+ Yrs of Exp,..)

Duration: 45 Days

Venue :
DURGA SOFTWARE SOLUTIONS,
Flat No : 202, 2nd Floor,
HUDA Maitrivanam,
Ameerpet, Hyderabad - 500038

Ph.No: +91 - 8885252627, 9246212143, 80 96 96 96 96

Syllabus:

MICROSOFT FABRICS

Module 1: Microsoft Fabrics Fundamentals

Module 2: Microsoft One Lake

Module 3: Fabric Lakehouse

Module 4: Fabric Data Factory

Module 5: Data Flow Gen2

Module 6: Pyspark Development

Module 7: Fabric Data Governance

Module 8: Data warehouse and Security

Module 9: Spark Structured Streaming

Module 10: Materialized Lake Views (MLV)

1. Microsoft Fabrics Fundamentals

• Why Microsoft Fabric?
• What is Microsoft Fabric?
• Hierarchy in Microsoft Fabric
• Roles in Microsoft Fabric
• Fabric Free Account
• Fabric Portal Overview

2. Microsoft One Lake

• What is OneLake
• Why OneLake
• Advantages of OneLake
• Manage your data - One Lake File Explorer

3. Fabric Lakehouse

• 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

4. Fabric Data Factory

• 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

5. Data Flow Gen2

• 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

6. Pyspark Development

• 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
• Notebook Utils 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

7. 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

8. Data warehouse and Security

• 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 T-SQL
• Gold Layer Business View using T-SQL
• T-SQL Functions
• T-SQL Stored Procedures
• Dynamic Management Views
• Query Insights View
• Visual Query Editor in Fabric Data Warehouse
• Integrating T-SQL 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

9. Spark Structured Streaming

• Introduction
• Spark Streaming Structure
• Stateless VS Stateful Transformations
• Checkpoint Location
• Output Modes
• Process Stream Data

10. Materialized Lake Views (MLV)

• Introduction
• What is MLV?
• Core Of MLV
• Why to use MLVs?
• Automatic Refresh in MLV
• How do MLVs work?
• Enable CDFs for MLVs
• Build Bronze Layer with MLVs
• Build Silver Layer with MLVs
• Build Gold Layer with MLVs
• Data Quality Checks & SQL MLV
• Data Lineage
• Optimal Refresh
• Schedule MLVs
• Debug MLVs
• Data Quality Report
• MLVs Limitations

11. Optimization in Fabrics

• Introduction
• Optimize Lakehouse
• Optimize Pipelines
• Optimize Warehouse
• Optimize Spark & Query
• Set Spark Configs
• Optimize Event stream
• Accelerated & Non-Accelerated Shortcuts