Abhishek Agrawal

UrbanPro Certified Tutor

For Microsoft Azure Training

Years of Experience in Microsoft Azure Training

8

Teaching Experience in detail in Microsoft Azure Training

I'm an Azure Data Engineer offering 10+ years of teaching experience and 6+ years IT experience in data engineering, data warehousing, machine learning, and business intelligence realm. I have completed my engineering (B.Tech) from NIT RAIPUR. -All Classes with Lab sessions and Daily Practice. -End to End Project Implementation using Azure. -Trained people in becoming Microsoft certified cloud developer from scratch. -Get online recording of classes with lifetime access. -Helped experienced IT people to secure good job in Azure cloud technology. -Providing support in interview preparation and Resume Building. -Support for fresher's to secure good jobs as Business Analyst, Data Analyst, Data Engineer in 2-3 Month of Training -Helped people to move from SSIS, SSRS, SSAS to Azure Cloud Enviornment. -Providing Microsoft CertificationTraining and Support. -Practice is key to success. -I believe in Practical Implementation instead of theoretical knowledge.

UrbanPro Certified Tutor

For Azure Data Factory Training

Years of Experience in Azure Data Factory Training

8

Teaching Experience in detail in Azure Data Factory Training

I'm an Azure Data Engineer offering 10+ years of teaching experience and 6+ years IT experience in data engineering, data warehousing, machine learning, and business intelligence realm. I have completed my engineering (B.Tech) from NIT RAIPUR. -All Classes with Lab sessions and Daily Practice. -End to End Project Implementation using Azure. -Trained people in becoming Microsoft certified cloud developer from scratch. -Get online recording of classes with lifetime access. -Helped experienced IT people to secure good job in Azure cloud technology. -Providing support in interview preparation and Resume Building. -Support for fresher's to secure good jobs as Business Analyst, Data Analyst, Data Engineer in 2-3 Month of Training -Helped people to move from SSIS, SSRS, SSAS to Azure Cloud Enviornment. -Providing Microsoft CertificationTraining and Support. -Practice is key to success. -I believe in Practical Implementation instead of theoretical knowledge.

Years of Experience in Azure Databricks Courses

10

Teaching Experience in detail in Azure Databricks Courses

I'm an Azure Data Engineer offering 10+ years of teaching experience and 6+ years IT experience in data engineering, data warehousing, machine learning, and business intelligence realm. I have completed my engineering (B.Tech) from NIT RAIPUR. -All Classes with Lab sessions and Daily Practice. -End to End Project Implementation using Azure. -Trained people in becoming Microsoft certified cloud developer from scratch. -Get online recording of classes with lifetime access. -Helped experienced IT people to secure good job in Azure cloud technology. -Providing support in interview preparation and Resume Building. -Support for fresher's to secure good jobs as Business Analyst, Data Analyst, Data Engineer in 2-3 Month of Training -Helped people to move from SSIS, SSRS, SSAS to Azure Cloud Enviornment. -Providing Microsoft CertificationTraining and Support. -Practice is key to success. -I believe in Practical Implementation instead of theoretical knowledge.

Years of Experience in Interview Skills Training

10

Years of Experience in Amazon Web Services Training

14

Teaching Experience in detail in Amazon Web Services Training

YouTube is full of videos, but where do you even begin? What should you learn? It’s overwhelming! That’s why this course is designed to save you time and effort, providing a clear, step-by-step roadmap to help you transition from a data analyst to a data engineer efficiently. Why this course is different: ✅ Structured Learning – No more random videos! Every lesson builds on the last, with homework and hands-on projects. ✅ Real-World Experience – Work on industry-grade projects, apply skills practically, and get access to practice notebooks. ✅ Scenario-Based Training – Master interview questions, confidently explain projects, and learn how to introduce yourself professionally. ✅ Resume & Interview Support – Get ready-made project explanations, sample resumes, and company-specific interview guidance. ✅ Personalized Mentorship – Small batch size (only 10 students) ensures focused attention and in-depth learning. From our team and industry expert, this course equips you with real-world knowledge, mentorship, and interview preparation—everything you need for a successful transition into data engineering!

Years of Experience in Snowflake Training

9

Teaching Experience in detail in Snowflake Training

Introduction & Fundamentals 1) Snowflake Architecture & Concepts Key Concepts & Architecture Cloud Platforms Snowflake Editions Overview of Key Features Overview of the Ecosystem 2) SnowSQL & User Management SnowSQL (CLI Client) - Installation, Configuring, and Usage Lab – SnowSQL Lab & Exercises Roles and Users in Snowflake 3) Virtual Warehouses & Storage Creation of Virtual Warehouses Resource Monitors Management and Alerts Creation of Databases and Schema Table Privileges Cache Layer 4) Data Management & Recovery Time Travel & Fail Safe - Recovery Zero Copy Cloning in Snowflake 5) Data Staging in Snowflake Types of Stages (Internal & External) Overview of Data Loading/Unloading Bulk Data Loading/Unloading from Local File System 6) Data Loading & Querying Querying Data in Staged Files Bulk Data Loads Loading Semi-Structured Data (JSON, XML) 7) Cloud Integrations AWS Integration Process AWS to Snowflake Data Loading Loading Semi-Structured Data from On-Premises to Cloud Advanced Snowflake Concepts 8) Continuous Data Loading Snowpipe & Configuration Continuous Data Loading using Snowpipe 9)Snowflake & Snowpark Overview of Snowflake & Snowpark Differences Between Snowpark and Spark Reading Data from Multiple Sources (CSV, JSON, Parquet, Delta, Iceberg) 10) Advanced Data Processing Using Snowflake Tables as Data Sources Handling Large-Scale Data Ingestion Optimizing Queries with Pushdown in Snowpark 11) Data Processing Optimization Partitioning, Bucketing & Indexing in Spark Building Reusable ETL Pipelines Handling Slowly Changing Dimensions (SCD Type 1, 2, 3) 12) Scheduling & Performance Optimization Scheduling ETL Jobs using ADF or AWS glue Optimizing Performance for Large-Scale Data 13) UDFs and Procedures Analytical Functions User Defined Functions Procedures 14) Performance Tuning Query Tuning Clustering Micro Partitions Materialized Views DBT & Data Governance 15) Introduction to DBT DBT Overview Set up DBT Cloud Connecting DBT to Snowflake Data loading into the data warehouse 16) GitHub Integration & IDE Version Control Data repository setup & connect to DBT cloud Fundamentals of DBT cloud IDE Connecting Repository & Warehouse 17) DBT Materialization Understanding Materializations Model Dependencies Table Type Materialization Incremental & Ephemeral Materialization 18) DBT Sources & Seeds Understanding Seeds and Sources Source Configuration Source Freshness & Validations 19) DBT Testing & Snapshots DBT Testing Framework Snapshots & Incremental Strategies 20) DBT Macros & Hooks Creating & Using Macros Hooks & Exposures Setting up a BI Dashboard in Snowflake 21) Data Security & Compliance Column-Level and Row-Level Masking Policies Working With Dates and Time Stamps Date and Time Stamp Conversions Data Pipelines, Airflow & Real-Time Project 22) Data Orchestration Creating ELT Pipeline, Connecting ADF to Snowflake using ODBC, JDBC & REST API Orchestration with ADF or AWS Glue or Airflow 23) Airflow Architecture & Snowflake Integration Installing & Configuring Apache Airflow Running Airflow Locally using Docker Architecture & Core Components (DAGs, Tasks, Operators, Hooks, Sensors) Airflow Scheduler & Executor Types Installing Snowflake Provider Package Configuring Airflow Connections to Snowflake 24) DAGs & Task Dependencies Understanding DAG Structure & Task Dependencies Using Snowflake Operators & Hooks SnowflakeOperator for running SQL queries SnowflakeHook for executing queries dynamically PythonOperator with Snowflake for custom processing BranchOperator for conditional workflows 25) Build a fully automated Snowflake Data Pipeline using Airflow Using dbt with Airflow & Snowflake 26) Real-World Use Case – Project Overview Explanation of the Project Planning the Data Pipeline Architecture 27) Project Implementation – Part 1 Data Ingestion using ADF & Airflow 28) Project Implementation – Part 2 Query Optimization & Performance Tuning Setting up BI Dashboards 29) Testing & Debugging Testing Debugging ETL Pipelines 30) Final Review & Certification Recap of Key Topics and Project discussion