This impeccable Azure Data Factory Training course is carefully designed for aspiring ETL Developers and Architects. This Azure Data Factory Training includes basic to advanced ETL Concepts, Data Warehouse (DWH) and Data Mashups / Data Flow concepts using SQL Server, Azure SaaS Components. This Azure Data Factory Training course also includes Azure SQL Database Migrations, Azure Storage, Azure Data Warehouse (ADW), Incremental Loads, Power Query, Azure Data Lake required for Big Data Analytics and Warehouse design with ONE Real-time Project.
PLAN A | PLAN B | PLAN C | |
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Azure DataFactory & Syanpse |
Power BI Azure DataFactory |
Power BI, Azure Data Engineer |
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Total Duration | 2 Weeks | 6 Weeks | 10 Weeks |
ADF : Azure Data Factory | ✔ | ✔ | ✔ |
ADF : Data Imports, ETL | ✔ | ✔ | ✔ |
ADF : Data Flows, Wrangling | ✔ | ✔ | ✔ |
ADF : Transformations, ETL | ✔ | ✔ | ✔ |
Synapse: Configuration, Loads | ✔ | ✔ | ✔ |
Synapse: ETL with ADF, DWH | ✔ | ✔ | ✔ |
Synapse: Performance Tuning | ✔ | ✔ | ✔ |
Synapse: MPP, cDWH, DIUs | ✔ | ✔ | ✔ |
Power BI: Report Design, Visuals | ❌ | ✔ | ✔ |
Power BI: M Lang, DX for ETL | ❌ | ✔ | ✔ |
Power BI: Report Server, Admin | ❌ | ✔ | ✔ |
ADB : Azure Data Bricks | ❌ | ❌ | ✔ |
ADB : Architecture, Data Loads | ❌ | ❌ | ✔ |
ADB : Run Spark Jobs, Pools | ❌ | ❌ | ✔ |
ADB : Workspace, Delta Tables | ❌ | ❌ | ✔ |
Cosmos : Configurations | ❌ | ❌ | ✔ |
Cosmos: Distribute Data, ETL | ❌ | ❌ | ✔ |
Cosmos: Integration with ADF | ❌ | ❌ | ✔ |
Cosmos: Structured Streaming | ❌ | ❌ | ✔ |
Total Course Fee * |
INR 9,000 USD 122 |
INR 17,000 USD 230 |
INR 31,000 USD 419 |
Azure Data Engineer Training Schedules | ||||
S No | Timings (IST) | Start Date | ||
---|---|---|---|---|
Regular Schedules [Mon - Fri] | ||||
1 | 7 AM - 8 AM | Jan 19th | Register | |
2 | 7 PM - 8 PM | Feb 1st | Register |
Azure Data Factory Training Schedules | ||||
S No | Timings (IST) | Start Date | ||
---|---|---|---|---|
Regular Schedules [Mon - Fri] | ||||
1 | 7 AM - 8 AM | Feb 2nd | Register | |
2 | 7 PM - 8 PM | Feb 1st | Register |
Power BI Training Schedules | ||||
S No | Timings (IST) | Start Date | ||
---|---|---|---|---|
Regular Schedules [Mon - Fri] | ||||
1 | 8 AM - 9 AM | Mar 9th | Register | |
2 | 6 PM - 7 PM | Feb 15th | Register | |
3 | 9 PM - 10 PM | Jan 19th | Register |
If above schedule does not work, opt for Azure Synapse Training Videos
Azure Data Factory Training Highlights :
✔ Azure Data Factory |
✔ Azure Databricks |
✔ Azure Synapse |
✔ Azure Cosmos DB |
✔ ADF Resources, Monitor |
✔ Power Query in ADF |
✔ Azure Storage Explorer |
✔ Azure Data Explorer |
✔ On-Premise Migrations |
✔ Big Data Storage |
✔ Performance Tuning |
✔ Security Management |
✔ Prepping, Ingestions |
✔ Spark Clusters, Python, Scala |
All Session Are Completely Practical & Real Time
1. Azure Fundamentals: What is Cloud? Advantages of Azure Cloud? IaaS, SaaS & PaaS. Azure Data Engineer Technologies, Job Roles. DP 200, 201 Exams Azure Account Registration and Free Trail Activation; Understanding Azure Resources and Resource Types; Creating Resource Groups in Azure Portal; | ||
2. Azure SQL Server: Azure Resources; Resource Groups; Azure SQL Server [Logical Server] Creation; Server Name Format and Firewall Rules; Azure Services Access with Firewall; Test Connections with SSMS Tool and Azure Data Studio Tool; Creating Azure SQL Databases in Portal, T-SQL; Tables, Data Inserts; | ||
3. Azure SQL DB Migrations: Azure SQL DB Migrations from OnPremise; Using Data Migration Assistant Tool; Migration Assessments; Deploy Schema & Migrate Data Options; Onpremise Versus Azure SQL DB Differences; Generating bacpac Files From SSMS Tool; Azure SQL DB Exports & Imports; |
Module 1 |
Module 2 |
Module 3 |
Ch 1: Azure Data Factory, Synapse Intro
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Ch 4: Azure Data Lake with ADF
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Ch 7: Incremental Loads with ADF - 2
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Ch 2: Azure Synapse Architecture
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Ch 5: On-Premise Data to Azure
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Ch 8: Mapping Data Flow in ADF
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Ch 3: Azure Data Factory Architecture
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Ch 6: Incremental Loads with ADF - 1
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Ch 9: Wrangling Data Flow in ADF
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Ch 10: ADF : End to End Implementation
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1. Azure Fundamentals: What is Cloud? Advantages of Azure Cloud? IaaS, SaaS & PaaS. Azure Data Engineer Technologies, Job Roles. DP 200, 201 Exams Azure Account Registration and Free Trail Activation; Understanding Azure Resources and Resource Types; Creating Resource Groups in Azure Portal; | ||
2. Azure SQL Server: Azure Resources; Resource Groups; Azure SQL Server [Logical Server] Creation; Server Name Format and Firewall Rules; Azure Services Access with Firewall; Test Connections with SSMS Tool and Azure Data Studio Tool; Creating Azure SQL Databases in Portal, T-SQL; Tables, Data Inserts; | ||
3. Azure SQL DB Migrations: Azure SQL DB Migrations from OnPremise; Using Data Migration Assistant Tool; Migration Assessments; Deploy Schema & Migrate Data Options; Onpremise Versus Azure SQL DB Differences; Generating bacpac Files From SSMS Tool; Azure SQL DB Exports & Imports; |
Mod 1: Azure Data Factory, Azure Synapse, Azure Data Share, Azure Key Vaults |
Mod 2: Azure Storage, Azure Data Lake Storage, Azure Data Lake Analytics, U-SQL |
Mod 3: Azure Databricks, Azure Cosmos DB, Azure Stream Analytics, NoSQL |
Ch 1: Azure Data Factory, Synapse Intro
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Ch 11: Azure Storage Concepts
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Ch 21: Azure Databricks Configurations
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Ch 2: Azure Synapse Architecture
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Ch 12: Azure Tables & Azure BLOB
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Ch 22: Databricks Notebooks, Spark Jobs
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Ch 3: Azure Data Factory Architecture
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Ch 13: Azure Files, Queues & Security
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Ch 23: Python Notebooks & Operations
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Ch 4: Azure Data Lake with ADF
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Ch 14: Azure Monitor, KQL, Power Shell
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Ch 24: Scala Notebooks, SQL Notebooks
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Ch 5: On-Premise Data to Azure
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Ch 15: Azure Stream Analytics, Event Hubs
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Ch 25: Databricks Jobs & Power BI
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Ch 6: Incremental Loads with ADF - 1
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Ch 16: Azure Data Lake Storage (ADLS)
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Ch 26: Azure Cosmos DB - Architecture
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Ch 7: Incremental Loads with ADF - 2
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Ch 17: ADLS Monitoring, Alerts
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Ch 27: Azure Cosmos DB Queries Level 1
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Ch 8: Mapping Data Flow in ADF
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Ch 18: Azure Key Vaults & ADL Analytics
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Ch 28: Azure Cosmos DB Queries Level 2
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Ch 9: Wrangling Data Flow in ADF
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Ch 19: Data Lake Analytics, U-SQL 1
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Ch 29: Azure Notebooks, Azure Functions
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Ch 10: ADF : End to End Implementation
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Ch 20: Data Lake Analytics, U-SQL 2
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Ch 30: Azure Cosmos Admin, Power BI
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Real-time Project @ Ecommerce Domain: Includes On-Premise Migrations with bac Files, Azure Storage Compoments, Azure Data Ingestions using Azure Data Factory; Big Data Storage with Azure Synapse and Azure Cosmos Database; Big Data Analytics using Azure Databricks and Azure Stream Analytics. This Real-time Project also includes End User Reporting with Power BI. Additionally includes Resume Support and DP 200, DP 201 Certification Guidance. |
Part 1: Power BI Report Design |
Part 2: ETL, Data Modeling, DAX |
Part 3: Power BI Cloud, Admin |
Ch 1 : POWER BI BASICS
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Ch 7 : POWER QUERY LEVEL 1
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Ch 13 : POWER BI CLOUD - 1
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Ch 2: BASIC REPORT DESIGN
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Ch 8 : POWER QUERY LEVEL 2
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Ch 14 : POWER BI CLOUD - 2
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Ch 3 : Visual Sync, Grouping
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Ch 9 : POWER QUERY LEVEL 3
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Ch 15 : EXCEL & RLS
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Ch 4 : Hierarchies, Filters
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Ch 10 : DAX Functions - Level 1
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Ch 16 : Report Server, RDL
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Ch 5 : Bookmarks, Azure, Modeling
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Ch 11 : DAX Functions - Level 2
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Ch 17: MSBI Integrations
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Ch 6 : Visualization Properties
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Ch 12 : DAX FUNCTIONS Level 3
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Ch 18 : REAL-TIME PROJECT
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