Course Highlights
🧠 In-Depth Curriculum
💻 100% Practical Training
📊 Weekly Learning Plan
🧩 Capstone Project
👨🏫 Mentor Support
🎓 Career Assistance
Azure Data Engineering Course
Duration 3 Months
Module 1
BI – Flow
- What is OLTP & OLAP?
- How to load data from OLTP to OLAP?
- What is ETL?
- Who converts textual OLAP data into reports?
- To whom BI teams share the reports?
- End-to-end flow of BI environment
- Roles & responsibilities of a BI Developer
Module 2
Azure Data Factory Overview at High Level
- What is Cloud
- What is Azure
- What is the difference between cloud services & on Premises?
- What is Azure Data Factory?
- What are all the Components required to Configure ADF?
- ADF Stands for?
- What is Linked Service?
- What are Data Sets in Azure Data Factory?
- What is Dataset?
- What is IR?
- Types of IR’s?
- What is Pipeline?
- What are Data flows?
- List of Transformations in Dataflow?
Module 3
Data Warehouse Concepts
- What is SCD?
- Types of SCD (1,2,3)
- Attributes required for SCD Type 2
- Dimensions & Facts
- Star Schema & Snowflake Schema
- Data Mart concepts
- Top-down & Bottom-up approaches
- Types of Dimensions & Facts
- ODS & EDWH
- OLTP vs OLAP
Module 4
Azure Cloud Account Service Configuration
- Cloud Services vs On-premises
- Cloud service providers
- What is Azure Cloud Service?
- Types of Subscriptions
- Free Account setup
- Pay-As-You-Go account setup
- Visual Studio subscription setup
- Subscription cost verification
- What is a Resource Group?
- How to create Recourse?
- How to configure ADF Recourse?
- What is Storage Account Recourse?
- How to Create Containers in Storage Account?
Module 5
Configuring Storage Accounts & Databases
- Creating Azure resources
- Configuring ADF resource
- Configuring Storage Accounts
- Creating containers
- Uploading files
- Copying files within blob storage
- SQL database configuration
- Reading SQL data
- SQL concepts (DDL, DML, joins, clauses)
- OLAP functions
Module 6
ADF Resource Configuration
- Steps to configure ADF
- ADF architecture
- ADF user interface
- ETL flow using ADF
- Creating Linked Services
- Creating datasets
- Creating pipelines
- Integration Runtime types (Azure IR, SHIR, SSIS)
Module 7
ADF with Data Flow Transformations
- Publishing objects to ADF repository
- Validating pipelines
- Debugging pipelines
- Monitoring pipelines
- Working with ADF activities (files & tables)
- Working with mapping data flows
- Source & Sink transformations
- Alter Row, Sort, Filter transformations
- Conditional Split & Aggregate
- Rank, Pivot, Unpivot
- Join & Lookup transformations
- Union & Derived Column
- Exists & Select transformations
- Surrogate Key & Window transformation
Module 8
SCD Configuration Using Data Flows
- SCD Type 1 implementation
- SCD Type 2 implementation
- Incremental & Delta load using ADF
- Azure Key Vault – secure secrets
- Key Vault keys and certificates
- Event-based, Tumbling, Schedule triggers
- Passing parameters dynamically
- Master → Child pipeline parameters
- Parameters vs Variables
Module 9
Azure Data Factory Activities
- Copy Data Activity
- Data Flow Activity
- Filter Activity
- For Each Loop Activity
- If Condition Activity
- Switch Activity
- Until Activity
- Get Metadata Activity
- Execute Pipeline Activity
- Lookup Activity
- Pipeline Parameters
Module 10
REALTIME USE CASES USING AZURE DATA FACTORY
- Copy multiple files from Blob to Blob
- Filter activity for selecting required files
- Dynamic copy using parameters
- Get source file names dynamically
- Count source files from folder
- Validate copied data (Unit Testing)
- Incremental copy using last modified date
- Copy data from AWS to Azure
- Migrate AWS S3 to ADLS Gen2
Module 11
INTERVIEW SUPPORT CLASSES
- One Retail & Real-time Project
- FAQ’s technical & non-technical
- Mock interviews in classes
- Flask web applications and APIs
- Resume preparation class
Module 12
Azure Databricks
- What is Databricks?
- Why Databricks is needed?
- Types of clusters
- Databricks File System (DBFS)
- Notebook utilities
- Widgets & parameter passing
- Mounting storage accounts
- SAS key & Service Principal
- Delta Lake concepts
- Reading & writing multiple data formats
- Spark functions (Agg, Math, Date)
- Jobs creation & scheduling
- Batch & real-time streaming
- Databricks CICD
Module 13
Azure Synapse Analytics
- Introduction to Azure SQL Data Warehouse
- Difference between Azure SQL & SQL Warehouse
- Synapse overall architecture
- Dedicated SQL pool
- Serverless SQL pool
- Spark pool
- CTAS (Create Table As Select)
- Polybase concepts
- Creating Dimensions & Facts
- Hash / Round Robin / Replicated distributions
- Stored procedures & views
Power Module
- Apache Spark Project
- Top Apache Spark Interview Questions
- Data Structures & Algorithms
Profile Optimisation
- Resume Building
- LinkedIn Optimisation
- Naukri Profile Optimisation
M1 Completed
START GIVING INTERVIEWS
SQL SERVER
Module 1
Introduction to DBMS
- File Management SystemAnd Its Drawbacks
- Intro to DatabaseManagement System (DBMS)
- Types of DBMS systems
- Network DBMS(NDBMS)
- Hierarchical DBMS (HDBMS)
- Relational DBMS (RDBMS)
Module 2
Introduction to SQL Server
- SQL Server Versions and History
- Connecting To Server
- Authentication Modes
- SQL Server Authentication Mode
- Windows Authentication Mode
- SQL Server Management Studio and Tools
Module 3
SQL Server Database Design
- Database Creation using GUI
- Database Creation using T-SQL Scripts
- DB Design using Files and File groups
- Pages and Extents
- Data File and Log File and Its features
Module 4
Business Integrity
- Why Business Integrity
- Features of Business Integrity
- Null / Not Null
- Default
- Candidate Keys
- Primary Key
- Unique Key / Alternate Keys
- Foreign Key
- Check Constraints
- Identity
Module 5
SQL Server Data Types
- Unicode Vs. Non-Unicode
- Char, Varchar and Varchar(Max)
- nChar, nVarchar and nVarchar(Max)
- Numerical Data Types
- Currency Data Types
- Binary Data Types
- GUID Data Type
- Timestamp Data Type
- Bit Data Type
- Spatial Data Type
Module 6
Introduction to SQL
- Introduction to SQL
- Simple Queries
- Filter Rows using Where Clause
- Filter Columns using Select Clause
- Sorting Data
- Concatenate Strings and Columns
- Group by and Aggregations
- Having Clause
- Top (n) and Top (n) Percent
- Union and Union All
- Intersect and Except
- ISNULL()
Module 7
Queries
- Simple Queries
- Filter Rows using Where Clause
- Filter Columns using Select Clause
- Sorting Data
- Concatenate Strings and Columns
- Working with Columns and Constants
- Group by and Aggregations
- Having Clause
- Top (n) and Top (n) Percent
- Union and Union All
- Intersect and Except
- ISNULL()
- Joins (Inner, Outer, Left, Right, Full, Self, Cross)
- Sub Queries (Single Row, Nested, Co-Related)
- Exists and Not Exists Functions
- Derived Tables
- Cube and Rollup Operators
Module 8
Built In Functions
- String Functions
- Data Conversion Functions
- Date and Time Functions
- Aggregate Functions
- Ranking Functions
- Common Table Expressions (CTE)
Module 9
Indexes
- Heap Vs Indexes
- Clustered Index
- Non-Clustered Index
- Filtered Index
- Covered Index
- Create, Alter and Drop Indexes
- Statistics
- Performance Tuning of Queries
Module 10
Views
- Purpose Of Views
- Creating, Altering and Dropping Views
- Updateable and Non-Updateable Views
- Encryption and SchemaBinding, with CheckOption Options in Views
- Indexed Views
Module 11
Intro to T-SQL Programming
- Declaring Variables
- Local and Global Variables
- Local and Global Temp Tables
- IF…. ELSE
- While Loop
- Return Statement
- Table Variable Vs. Temp Tables
- Exception Handling with Try… Catch Blocks
Module 12
Stored Procedures
- Need for Stored Procedures
- Creating, Altering and Dropping Stored Procedures
- Optional Parameters
- Input and Output Parameters
- Nested Stored Procedures
- Re-Compiler Stored Procedures
- Advantages and Disadvantages of Stored Procedures
- Writing Complex Stored Procedures
- Writing Stored Procedures with Cursors
Module 13
Cursors
- Need for Cursors
- Types Of Cursors
- Forward_Only and Scroll Cursors
- Static, Dynamic and Keyset Cursors
- Visibility of Cursors
Module 14
User Defined Functions
- Need for UDFs
- Creating, Altering and Dropping
- Types Of User Defined Functions
- Scalar Functions
- Inline Table Valued Functions
- Multi Statement Table Valued Functions
Module 15
Triggers
- Purpose of Triggers
- Creating, Altering and Dropping Triggers
- Types of Triggers
- For or After Triggers
- Instead Of Triggers
- Magic Tables (Inserted, Deleted)
- Rollback in Triggers
Module 16
Transactions (SQL Server)
- Introduction
- Begin Transaction
- Commit Transaction
- Rollback Transaction
- Save Transaction
- Role Of Log File In Transaction Management
- Implicit Transactions
- Explicit Transactions
Power Module
- Apache Spark Project
- Top Apache Spark Interview Questions
- Data Structures & Algorithms
Profile Optimisation
- Resume Building
- LinkedIn Optimisation
- Naukri Profile Optimisation
M1 Completed
START GIVING INTERVIEWS
PYTHON
Module 1
Python Core
- Introduction of python and comparison with other programming languages
- Installation of Anaconda Distribution and other python IDE
- Python Objects, Numbers & Booleans, strings, Container objects, Mutability of objects
- Conditions (if else , if –elif-else)
- Loops (while, for)
- Break and Continue Statements
- Operators - Arithmetic, Bitwise, comparison and Assignment
- Operators, Operators Precedence and associativity.
- Range functions
Module 2
String Objects and collections
- String object basics
- String methods
- Splitting and Joining Strings
- String format functions
- List object basics
- List methods
- List as stack and Queues
- List comprehensions
Module 3
Tuples, Set, Dictionaries & Functions
- Tuples, Sets, Dictionary Object basics, Dictionary
- Object methods, Dictionary View Objects
- Functions basics, Parameter passing, Iterators
- Generator functions
- Lambda functions
- Map, Reduce, filter functions
Module 4
OOPS concepts & Working with Files
- OOPS basic concepts
- Creating classes and Objects
- Inheritance, Multiple Inheritances
- Working with files
- Reading and writing files
- Buffered read and write
- Other File methods
Module 5
Modules, Exception Handling & Database Programming
- Using Standard Module
- Creating new modules
- Exceptions Handling with Try-except
- Creating, inserting and retrieving Table
- Updating and deleting the data
- FILE
Module 6
Flash and Api’s
- Flask introduction
- Flask Application
- Open link Flask
- App Routing Flask
- URL Building Flask
- HTTP Methods Flask
- Templates Flask
Module 7
Visualisation
- Matplotlib
- Seaborn
- Plotly
- Cufflinks
Module 8
Python Pandas
- Python Pandas - Series
- Python Pandas – Data Frame
- Python Pandas - Panel
- Python Pandas – Basic Functionality
- Function Application
- Python Pandas – Re-indexing
- Python Pandas - Iteration
- Python Pandas - Sorting
- Working with Text Data
- Options & Customization
- Indexing & Selecting Data
- Module 8 Python Pandas
- India’s No.1 Online Training Institute
- Statistical Functions
- Python Pandas - Window Functions
- Python Pandas - Date Functionality
- Python Pandas – Time delta
- Python Pandas – Categorical Data
- Python Pandas - Visualization
- Python Pandas – IOTools
Module 9
Python Numpy
- NumPy - Ndarray Object
- NumPy - Data Types
- NumPy – Array Attributes
- NumPy - Array Creation Routines
- NumPy - Array from Existing Data
- Array from Numerical Ranges
- NumPy - Indexing & Slicing
- NumPy - Advanced Indexing
- NumPy – Broadcasting
- NumPy - Iterating Over Array
- NumPy - Array Manipulation
- NumPy - Binary Operators
- NumPy - String Functions
- NumPy - Mathematical Functions
- NumPy - Arithmetic Operations
- NumPy - Statistical Functions
- Sort, Search & Counting Functions
- NumPy - Byte Swapping
- NumPy - Copies & Views
- NumPy - Matrix Library
- NumPy - Linear Algebra
Module 10
Exploratory Data Analysis
- Feature Engineering and Selection
- Building Tuning and Deploying Models
- Analyzing Bike Sharing Trends
- Analyzing Movie Reviews Sentiment
- Customer Segmentation and Effective Cross Selling
- Analyzing Wine Types and Quality
- Analyzing Music Trends and Recommendations
- Forecasting Stock and Commodity Prices
Power Module
- Apache Spark Project
- Top Apache Spark Interview Questions
- Data Structures & Algorithms
Profile Optimisation
- Resume Building
- LinkedIn Optimisation
- Naukri Profile Optimisation
M1 Completed
START GIVING INTERVIEWS
WEEK 1 – 3
- Big Data – The Big Picture
- Distributed Storage & Processing Fundamentals
WEEK 4 - 9
- Apache Spark In-Depth
WEEK 10 - 11
- Apache Spark Optimizations
WEEK 12 - 13
- Apache Spark Optimizations
Course Fee
For Students accessing the course from India
(Duration: 7 Months – Validity: 2 Years)
Data Science (AI/ML) Payment Link with 15% Discount:
Data Analytics using PowerBI Payment Link with 15% Discount:
Azure Data Engineering Payment Link with 15% Discount:
FullStack Python payment Link :
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Our Alumni work at eminent Big data companies and progressive Startups
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Our Students Testimonials
Harikrishna K.
I attended MSBI(SSIS,SSAS),SQL Server ,Power BI ,Data Warehouse Courses by Under Bhaskar Jogi Sir Training. Bhaskar ,for MSBI and power BI learners very good platform Go online Trainings Institute .I learned a lot from Bhaskar sir’s teaching ,Thank You So Much Sir.
Arjun Sudheer
I am really impressed with the way Bhaskar sir teaches each and every concept! He is very passionate about teaching and that can be experienced with the way he teaches each topic, with his teaching anyone can learn any technology with ease! He teaches each and every concept .
Rajsekhar Koneru
I have completed power bi ,SQL server, Data Warehouse and SSIS with Bhaskar Jogi sir. The training is fabulous. I never seen this kind of training in my life. Thanks a lot Bhaskar sir. I recommend this training to all students who wanted a job in IT sector.
Sai Kumar Reddy
Am attending the PBI, DWH, SQL Server by Bhaskar Jogi Sir. I strongly recommend this course and the teaching by Bhaskar Jogi is very easy to understand with real time case study. Even non IT people can learn with the teachings of Bhaskar Jogi and get into the IT Industry.
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