
Power BI is an awesome, colourful technology that can help us to understand the data, get the actual insights and report / showcase to the customers with ease. Using Power BI, we can design interactive visualizations, dashboards, apps and more.. !
✅ Power BI Desktop & Service
✅ Data Modeling, DAX Functions
✅ Power Query (M), Parameters
✅ Interactive Dashboards, Apps
✅ Big Data Access, DAX
✅ Dynamic Row Level Security (RLS)
✅ Power BI with Azure & Fabric
✅ Power BI Deployment, IAM
✅ End-to-End Real-Time BI Project
✅ 1:1 Mentorship, Interview Guidance
Power BI Training
Course Contents:
Module 1 : Microsoft SQL (TSQL)
Ch 1: SQL SERVER INTRODUCTION
- Database Introduction
- Types of Databases
- Need for & ETL, DWH
- BI Implementations
- SQL Server Advantages
- Version, Editions of MSSQL
- Data Analyst Job Roles
Ch 2: SQL SERVER INSTALLATIONS
- SQL Server 2019, 2017
- SSMS Tools Installation
- Database Engine (OLTP)
- SCM, Configuration Tools
- Instance Types, Uses
- Authentication Modes
- Collation, File Stream
Ch 3: SQL BASICS – 1
- Need for Databases, Tables
- Need for SQL Commands
- DDL, DML & DQL Statements
- Database Creation @ GUI
- Data Operations @ GUI
- Session ID, SQL Context
- DB, Tables, Data @ SQL
Ch 4: SQL BASICS – 2
- DDL Variants in MSSQL
- DML Variants in MSSQL
- INSERT & INSERT INTO
- SELECT & SELECT INTO
- Basic Operators in SQL
- Special Operators in MSSQL
- ALTER, ADD, TRUNCATE, DROP
Ch 5: Data Imports, Schemas
- Data Imports with Excel
- ORDER BY & UNION
- UNION ALL For Sorting Data
- Creating, Using Schemas
- Real-world Banking Database
- Table Migrations @ Schemas
- 2 Part, 3 Part & 4 Part Naming
Ch 6 : Constraints, Index Basics
- Need for Constraints, Keys
- NULL, NOT NULL, UNIQUE
- Primary Key & Foreign Key
- RDBMS and ER Models
- Identity Property, Default
- Clustered Index, Primary Key
- Non Clustered Index, Unique
Ch 7: Joins & Views Basics
- JOINS: Purpose. Inner Joins
- Left / Right / Full Outer Joins
- Cross Joins, Query Tuning
- Creating & Using Views
- DML, SELECT with Views
- RLS : WITH CHECK OPTION
- System Views & Metadata
Ch 8: Functions(UDF), Data Types
- Using Functions in MSSQL
- Scalar Value Functions
- Inline & Multiline Functions
- Date & Time Functions
- String, Aggregate Functions
- Data Types : Integer, Char, Bit
- SQL Variant, Timestamp, Date
Ch 9: Stored Procedures,Models
- Stored Procedures & Usage
- Creating, Testing Procedures
- Encryption, Deferred Names
- SPs for Validations, Analysis
- System SPs, Recompilation
- Normal Forms & Types
- Data Models, Self-References
Ch 10: Triggers, Temp Tables
- Need for Triggers
- DDL & DML Triggers
- Using Memory Tables
- Data Replication, Automation
- Local & Global Temp Tables
- Testing & Using Temp Tables
- SELECT .. INTO & Bulk Loads
Ch 11: DB Architecture, Locks
- Planning VLDBs : Files, Sizing
- Filegroups, Extents & Types
- Log Files : VLF, Mini LSN
- Table Location, Performance
- Schemas, Transfer, Synonyms
- Transactions Types, Lock Hint
- Query Blocking Scenarios
Ch 12 : Cursors & CTEs, Links
- Cursors : Realtime Use
- Fetch & Access Cursor Rows
- CTEs for SELECT, DML
- CTEs: Scenarios & Tuning
- Linked Servers, Remote Joins
- Linked Servers: MSDTC, RPC
- Tuning Remote Queries
Ch 13: Merge, Upsert & Rank
- Need for Merge in ETL
- Incremental Loads with SQL
- MERGE and RANK Functions
- Window Functions, Partition
- Identify, Remove Duplicates
Ch 14: Grouping & Cube
- Group By & HAVING
- Cube, Rollup & Grouping
- Joins with Group By
- 3 Table, 4 Table Joins
- Query Execution Order
Ch 15: Self Joins, Excel Analysis
- Self Joins & Self References
- UNION, UNION ALL
- Sub Queries with Joins
- IIF, CASE, EXISTS Statements
- Excel Analytics, Pivot Reports
Module 2: Power BI
Ch 1 : Power BI Introduction
- Reporting Basics & Types
- Interactive,Analytical Reports
- Paginated Reports (RDL)
- Power BI Eco System
- Power BI Tools,Service,Server
- Need for Power Query (M)
- Need for DAX & Cloud
Ch 2: Power BI Basic Reports
- Power BI Desktop Installation
- Basic Report Design (PBIX)
- Data View, Data Models
- Data Points, Aggregations
- Focus Mode, Spotlight, Exports
- ToolTip, PBIX and PBIT
- Visual Interactions & Edits
Ch 3 : Grouping, Hierarchies
- Creating Groups in Power BI
- Groups : Creation & Usage
- Group Edits Options
- Bins & Bin Size, Bin Count
- Hierarchies: Creation, Use
- Drill Down, Drill Up
- Conditional Drill Down
Ch 4 : Visual Sync, Filters
- Slicer & Single Select
- Multi Select Options
- Integer, Character Slicers
- Visual Sync with Slicers
- Filters: Visual, Page, Report
- Drill Thru Filters & Usage
- Basic, Top & Advanced
- Clear Filter Options, Resets
Ch 5 : Bookmarks, Big Data
- Bookmarks Creation & Usage
- Visual Interactions, Bookmarks
- Images : Actions, Bookmarks
- Big Data Access with Power BI
- Storage Modes: Direct Query
- Import & Performance Impact
- Formatting & Data Refresh
- Summary, Date Time Formats
Ch 6 : Power BI Visualizations
- Chart and Bar Visuals
- Line and Area Charts
- Maps, TreeMaps, HeatMaps
- Funnel, Card, Multrow Card
- PieCharts & Settings
- Waterfall, Sentiment Colors
- Scatter Chart, Play Axis
- Infographics, Classifications
Ch 7 : Power Query Level 1
- Power Query (Mashup)
- ETL Transformations in PBI
- Power Query Expressions
- Table Combine Options
- Merge, Union All Options
- Table Transformations
Ch 8 : POWER QUERY LEVEL 2
- Any Column Transformations
- String / Text Transformations
- Numeric Analytics & Mashup
- Date Time Transformations
- Add Column Transformations
- Expressions and New Columns
Ch 9 : POWER QUERY LEVEL 3
- Parameters in Power Query
- Static Parameters, Defaults
- Dynamic Dropdowns, Lists
- Linking with Table Queries
- Column From Examples
- Step Edits, Type Conversions
Ch 10 : Power BI Cloud – 1
- Power BI Cloud Concepts
- Workspace Creation, Usag
- Report Publish & Edits
- Semantic Models in Realtime
- Dashboard Creation, Usage
- Clone, Share, Subscribe
- Q&A, Lineage, Settings
Ch 11 : Power BI Cloud – 2
- Data Gateways, Data Refresh
- Data Source Configurations
- Data Refresh & Scheduling
- Gateway Optimizations
- Semantic Model Optimizations
- Report Optimizations
- Dashboard Optimizations
Ch 12 : Power BI Cloud – 3
- Power BI Apps, Shares
- App Sections & Options
- App Updates, Security
- Excel Analytics
- Data Explorer Option
- Sharing, Subscriptions
- Alerts, Metrics, Insights
Ch 13 : Report Server & DAX
- Power BI Report Server
- Report Database, TempDB
- Web Service & Server URL
- Paginated Reports (RDL)
- Report Builder Tool Usage
- DAX : Purpose, Realtime Use
Ch 14: DAX Level 2
- DAX Measures Creation, Use
- DAX Functions: IIF, ISBLANK
- SUM, CALCULATE Functions
- DAX Cheat Sheet : Examples
- Quick Measures in Power BI
- Running Totals, Filters
Ch 15 : DAX Level 3
- Star Rating Calculations
- Data Models & DAX
- Star & Snowflake Schemas
- Dimensions, Fact Tables
- DAX Expressions & Joins
- DAX Variables, Usage
Ch 16 : DAX Level 4
- Dynamic Report with DAX
- SELECTED MEMEBER
- Time Intelligence with DAX
- PARALLELPERIOD, DATE
- DAX with Big Data
- Big Data Analytics
Ch 17 : Realtime Project – Requirements
- Customer Requirement
- Scope of the Project
- End User Take Aways
- Implementation Phases
- Data Sources & Types
- Data Sheets, Project Planning
Ch 18 : Realtime Project – Implementation
- Excel Data Sources
- SQL Database Sources
- Azure SQL DB Sources
- AVRO, JSON, PDF Sources
- Reports, Dashboards, Apps
- Project Solution & FAQs
Module 3: Fabric Data Engineer
Ch 1: Fabric Introduction
- Need for Fabric, Big Data
- Fabric Data Engineering Model
- Fabric Components (Items)
- Microsoft Fabric: Advantages
- Cloud Warehouse Uses
- Benefits of Fabric Over Azure
- Azure Versus Fabric DWH
Ch 2: Fabric Account, Workspace
- Need for Fabric Workspace
- Workspace Creation Process
- Pins and New Items
- Item Categorization
- ETL, Storage, Analytical
- Streaming, Monitoring
- Compute & Separation
Ch 3: Fabric Architecture
- Intelligent Data Foundation
- Polaris Distributed Engine
- Stateless & Stateful
- Cache, Metadata, Xact & Data
- Fabric Tasks, Inputs & DAG
- State Machine & Statistics
- Hot Spot Recovery
Ch 4: Fabric Warehouse
- Fabric Warehouse Creation
- Fabric Warehouse Features
- Fabric Warehouse Properties
- Fabric Warehouse Limitations
- DWH Internal Operations
- Default Schemas & Objects
Ch 5: Fabric Data Types
- Realtime use of Fabric Houses
- Exact, Approximate Numbers
- Date and Time Data Types
- Fixed & Variable Length
- Binary & String Data Types
- Fabric Type Limitations
Ch 6: SSMS Connections
- Warehouse SQL Connection
- Database Engine Server
- Multi Factor Authentication
- Warehouse Artifacts
- Executing .SQL Scripts
- Testing Fabric Artifacts
Ch 7: Fabric Caching
- Fabric Caching Process
- In-memory Cache, Disk Cache
- Cache Types: LRU /MRU
- Cold Cache / Cold Run
- Realtime use of Caching
- Performance Advantages
- Warehouse Optimizations
Ch 8: Fabric Statistics
- Query Engine Options
- Statistics Types
- Leverage Statistics
- Auto, Manual Statistics
- Update Statistics
- Statistics Consistency
- Statistics Lists & Reports
Ch 9: Time Travel
- Continuous Data Protection
- Data Storage, Retention
- FOR TIMESTAMP AS OF
- Time Travel Scenarios
- Time Travel Implementation
- Time Travel on Queries
- Time Travel Limitations
Ch 10: Aggregated Data Store
- Options for Data Aggregations
- Save As table, Save As View
- Single Table Aggregations
- Multi Table Aggregations
- Dynamic Conditions
- Parameterized Aggregations
Ch 11: Zero Copy Cloning
- User Layer, Storage Layer
- Cloning & Parquet Files
- Synapse Data Warehouse
- Data History Retention
- Point In Time , Schema Level
- Zero Copy Cloning Limitations
Ch 12: Fabric Security
- Workspace Security
- Warehouse Security
- Item Security & Roles
- Adding AD Users
- Item Security Limitations
- MFA & Client Security
Ch 13: Fabric Data Factory
- ETL Implementation Options
- Need for Fabric Data Factory
- ETL Operations in FDF
- Data Sources, Transformations
- Data Destinations (Sinks)
- Creating Pipelines
Ch 14: Fabric Pipelines
- Activities and Connections
- Gateways & OnPrem Access
- Data Sets & Activity Sets
- Data Activator & Alerts
- Run ID & Monitoring
- Pipeline Creation, Verification
- Activity Check, Schedule
Ch 15: Fabric Pipelines Design
- Creation Options for Pipelines
- Azure SQL DB Data Loads
- Creating Data Sets
- RRR Transformations
- Copy Command Usage
- Internal Staging (Workspace)
- Data Loads to FDWH
Ch 16: Fabric Aggr Data Loads
- Aggregation Scenarios
- Creating Views in TSQL
- Using Views in FDF Pipelines
- Using Pipeline Editor
- Data Loads to Warehouse
- Pipeline Verifications
Ch 17: ETL Staging
- Staging : Advantages
- Caching & Storing Concept
- Staging Types in Fabric
- Workspace & External
- External Stages in Pipelines
- Compressions & Advantages
- Pipeline Trigger, Monitor
Ch 18: OnPrem Gateways
- Need for On_Premi Gateway
- Installing & Configuring
- Authentication, Usage
- OnPremises Connections
- Pipelines for Data Loads
- Warehouse Data Storage
- Data Refresh with Gateways
Ch 19: Fabric Lakehouse
- Need for Fabric Lakehouse
- Files and Tables Storage
- Data Sources: Parquet Files
- Transformation Options
- Direct Lake Concepts
- Lakehouse Consumption
- Lakehouse Real time Use
Ch 20: Lakehouse File Loads
- Creating Lakehouse
- Copy Data Wizard
- Azure SQL Database Source
- File Data Loads in Lakehouse
- Concurrency & Batch Count
- Pipeline Execution Test
- Pipeline Monitor Check
Ch 21: Lakehouse Aggr Loads
- Aggregated Data Store
- Plan & Design Aggregations
- Testing Aggregations
- Pipelines for Data Compute
- Data Copy Options
- Pipeline Optimizations
- Data Loads and Verification
- Pipeline Execution Tests
- Pipeline Monitor Check
Ch 22: MultiTable Loads in LH
- Table Loads Connections
- Data Load in Lakehouse
- Using Copy Data Wizard
- Data Store in Lakehouse
- View Run History, Executions
- SQL End Points & Access
- Lakehouse Schemas
Ch 23: Lakehouse Visual Queries
- Visual Query Interface
- Visual Editor & Tables / Views
- Merge, Remove, Sort Tfns
- Data Preview, Save As Table
- Save As View : Advantages
- Using Schemas, Identifiers
- TDS Packets & Transfer Units
Ch 24: File Explorer
- Installing One Lake Explorer
- Autocreation of Folders
- Workspace Directories
- Warehouse Directories, Logs
- Lakehouse Folders, Files
- Lakehouse Uploads
- Explorer Tool Limitations
Ch 25: Power Query Level 1
- Power Query Concept
- Need for Power Query
- Data Flow Gen 1
- Data Flow Gen 2
- Power Query Items
- Differences with Copy Activity
- ETL, ELT Process
Ch 26: Power Query Level 2
- Data Flow Gen2 Operations
- PQ Online Editor
- Working with Binary Content
- Detailed Data Options
- Data Cleansing Options
- Step Names, Aggregations
- Warehouse Data Loads
Ch 27: Power Query Level 3
- Binding Power Query Steps
- Edit / Delete Steps
- Optimizing Power Query
- ETL & ELT with Power Query
- Advanced Editor
- M Language Expressions
- Duplicate / Reference Queries
Ch 28: Fabric Notebooks
- Need for Notebooks
- Fabric Notebook Types
- Get / Prep / Analyze
- Sessions, Markdown Folding
- Standard, High Concurrency
- Magic Command
- Freeze Cells
Ch 29: Spark SQL Notebooks
- Creating Environment
- Creating Spark Clusters
- Spark Cluster Compute
- SQL Analytics in Notebooks
- Visual Query Vs SQL
- Cell Execution Options
- Magic Command Usage
Ch30: PySpark Notebooks
- Creating / Using Environment
- PySpark Notebook Sessions
- Reading Source Data
- Data Prep & Aggregations
- Data Loads, Analytics
- Cell Execution Options
- Markdown Cells
Ch 31: StreamHouse, KQL
- Need for Stream House
- Auto creation of KQL
- Manual KQL Databases
- Verification & Usage
- Differences with Warehouse
- Differences with Lakehouse
Ch 32: KQL Query Sets
- KQL Database ExtractionFile Imports – on Premises
- Metadata Edit Options
- Query Analytics
- Exports, Visualizations
- Query Sets Versus Notebooks
Ch 33: Fabric Data Activator
- Need for Alerts, Notifications
- Fabric Data Activator Options
- Alert Conditions, Thresholds
- Email Notifications
- Events & Notifications
- Edit / Enable / Disable
Ch 34: Model Layouts
- Need for Layouts
- Creating Model Layouts
- Adding Refences, Keys
- Power BI Semantic Models
- Creating Report Items
- Using Power BI Desktop
Ch 35: Azure Synapse Migrations
- Azure Synapse DWH
- Azure Synapse Connections
- Migrating to Fabric
- Compatibility Checks
- Synapse Vs Fabric Warehouse
- Fabric DWH Advantages
Ch 36: DP 700 Exam Guidance
End to End Realtime Project: Ecommerce Domain
SQL SCHOOL
24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.
#Top Technologies
Power BI Training FAQ's
What is Power BI Job Role?
Power BI professionals are responsible for designing, developing, and publishing interactive dashboards, reports, and business intelligence solutions. They integrate data from various sources, build data models, apply DAX (Data Analysis Expressions), and create compelling visualizations that enable organizations to make data-driven decisions. Power BI developers also collaborate with stakeholders to gather requirements, ensure data security, and optimize report performance for both desktop and cloud environments.
What are the Job Roles of an Power BI?
💼 Top Job Roles:
1️⃣ Design and build interactive dashboards, reports, and KPI scorecards
2️⃣ Create data models and write DAX queries for business metrics
3️⃣ Integrate and transform data from multiple sources (SQL, Excel, APIs, etc.)
4️⃣ Develop and maintain datasets, dataflows, and data gateways
5️⃣ Collaborate with business teams to define reporting requirements
6️⃣ Optimize report performance and ensure governance in Power BI Service and more..!
What does our Power BI Training course contain?
The course is carefully curated with below module:
👉🏻Module 1: MSSQL & TSQL Queries
👉🏻Module 2: Snowflake
👉🏻Module 3: Fabric Data Engineer
Who can join this course?
Freshers aiming to enter the BI, reporting, or analytics domain
Business analysts looking to automate and enhance reporting
Data professionals upgrading skills to modern visualization tools
IT and non-IT professionals interested in data storytelling
Anyone wanting to create professional dashboards without heavy coding
No prior coding experience is needed. The course teaches everything from basics to advanced concepts in a step-by-step practical approach.
What training modes are available?
Option 1: LIVE Online Training (100% Interactive, step by step, assignments)
Option 2: Self Paced Videos (100% practical, step by step with concept wise assignments)
You may choose any one of these options, same curriculum!
I (Trainer) shall be available for doubts and clarifications, assignment check and review.
Why should I choose SQL School for Power BI training?
👉🏻 Every session is Practical, Step by Step with Concept wise FAQs !!
👉🏻 100% results with on-time practice. Daily Tasks for every session.
👉🏻 Concept wise tasks be submitted before next class for Job Waiters / Starters.
👉🏻 Concept wise tasks due for submission by Weekends for Working Professionals.
Why Choose SQL School
- 100% Real-Time and Practical
- ISO 9001:2008 Certified
- Concept wise FAQs
- TWO Real-time Case Studies, One Project
- Weekly Mock Interviews
- 24/7 LIVE Server Access
- Realtime Project FAQs
- Course Completion Certificate
- Placement Assistance
- Job Support
- Realtime Project Solution
- MS Certification Guidance