From Analyst to Data Enabler

Power BI + Microsoft Fabric
Level Up Your Reporting — Build Cloud-based Reporting Systems

If your organization is moving toward Microsoft Fabric or enterprise-scale BI, this course is your launchpad. You'll learn how to connect Power BI to OneLake, work with governed datasets, and deliver cloud-ready dashboards that scale across teams. Designed for BI and reporting professionals, no IT background or coding required.

Tools You'll Master

Data Engineering

Microsoft Fabric

Visualization Tool

Power BI

Data Modeling Tools

Power Pivot , DAX

Data Transformation Tool

Power Query

Data Warehousing & Querying Tool

MS-SQL

What You’ll Achieve in Just 4 Weeks with Microsoft Fabric Training?

Design scalable cloud-based reports using Power BI and Microsoft Fabric.

Integrate Power BI with OneLake for real-time data access and insights.

Create cloud-native dashboards that drive data-driven decisions.

Automate reporting workflows for efficiency and accuracy.

Collaborate seamlessly with teams using shared, trusted datasets.

Elevate your role in data strategy and business intelligence.

What You’ll Achieve in Just 4 Weeks with Microsoft Fabric Training?

Design scalable cloud-based reports using Power BI and Microsoft Fabric.

Integrate Power BI with OneLake for real-time data access and insights.

Create cloud-native dashboards that drive data-driven decisions.

Automate reporting workflows for efficiency and accuracy.

Collaborate seamlessly with teams using shared, trusted datasets.

Elevate your role in data strategy and business intelligence.

Ideal For:

Finance & Operations

who want to deliver cloud-based reporting aligned with enterprise data models.

Reporting Professionals

looking to move beyond spreadsheets and connect Power BI to OneLake.

Data Analysts

who want to build scalable dashboards on governed, trusted datasets.

Business Analysts

aiming to work with real-time data and deliver insights across departments.

BI Team Members

who need to collaborate with IT on Microsoft Fabric implementations.

Power BI Users

ready to evolve into cloud-first, enterprise-ready reporting professionals.

A snapshot of what you'll be learning in 4-weeks.

Course Syllabus Overview

Power BI

Building Blocks of Power BI

Visualizations
Datasets
Reports
Dashboards
Tiles

Building Your First Power BI Report

Connect to Data Sources in Power BI Desktop
Clean and Transform Your Data With the Query Editor
Create a report in Power BI Desktop
Publish the report in the Power BI service

Data Modelling with Power BI

Fundamentals of Modelling
How to Manage Your Data Relationships
Create Calculated Columns
Optimizing Data Models for Better Visuals
Create measures and work with time-based functions
Create Calculated Tables
Explore Time-Based Data

Visualizations

Create and Customize Simple Visualizations

Building compelling data visualizations

Identify metrics and pair them with appropriate data visuals
Using slicers
Creating Map Visualizations
Creating Tables and Matrixes
Creating Waterfall and Funnel Charts
Using Gauges and Single Number Cards
Charting Options including Formatting with Colors, Shapes, Text Boxes, Images, etc.

Designing User-friendly reports

Customize themes
Create versatile layouts for your reports
Design principles to reduce noise and highlight data stories

Creating interactive reports for data exploration

Filtering & drilling for insights
Difference between filters & slicers
Filter pane for reporting needs

Power Query

Overview

Introduction
Loading & Refresh
Combine data from multiple data sources

Data Transformation

Editing Queries Created with Power Query
Editing Column Headers in Power Query
Splitting Column Data with Power Query
Sorting Data
Multi-Level Sorting
Filtering Data
Aggregate data from a column
Insert a custom column into a table
Merge columns
Remove columns
Remove rows with errors
Promote a row to column headers
Transforming Text Values
Replacing Data
Using the Fill command
Pivot and Unpivot Column
Transpose Query Data
Pivot Column Command in Action
Unpivot Columns Command
Grouping Data
Create a Duplicate Query
Group and Summarize Data
Advanced Data Grouping
Working with multiple sources in Power Query
Multiple Excel Tables
Expand a column containing an associated table
Understanding Table Relationships
Merging Queries

Loading Power Query Data to Destinations

Familiarity with the Load & Refresh Settings
Loading it to Workbook
Loading it to Data Model

DAX Functions

Overview

What is DAX?
Data Types
Table-Valued Functions
Building a Calendar Table
Date and Time Functions
Filter Functions
Information Functions
Logical Functions
Mathematical and Trigonometric Functions
Statistical Functions
Text Functions
Time Intelligence Functions
Creating Advanced DAX Measures With Advanced DAX Functions

Creating Advanced Dax Measures With Advanced Dax Functions

Calculate()
All()
Filter()
IF()
Switch()
SumX()

Evaluation Context

Filter Context
Row Context
Using RELATED in a Row Context
Filters and Relationships
USERELATIONSHIP

Hierarchies in DAX Querying with DAX Relationships

One-to-Many Relationships
Many-to-Many Relationships

Advanced DAX Functions

ADVANCED DAX FUNCTIONS ADVANCED CONTEXT CONCEPTS

Understanding and Debugging Context Transition
Expanded Tables and Filter Propagation
Using VAR for Performance and Clarity
Using TREATAS() to Apply Filters Between Unrelated Tables
Virtual Relationships using DAX
Shadow Filters and Filter Overriding Techniques

ADVANCED CALCULATION PATTERNS

Running Totals with Custom Filter Logic
Rolling Averages (e.g., 7-day, 12-month)
Year-over-Year (YoY), Quarter-over-Quarter (QoQ), MoM with Non-Standard Calendars
Top N Reporting with Others Grouping
Parent-Child Hierarchy Navigation using PATH, PATHITEM, PATHLENGTH
Budget vs. Actual Comparison Patterns
Custom Grouping (Bucketing) in DAX

ADVANCED TIME INTELLIGENCE

Semi-Additive Measures (e.g., Closing Balance, Opening Balance)
Workdays and Custom Holiday Calendars
Dynamic Period Selection (MTD, QTD, YTD) based on Slicers
Cumulative Totals Across Multiple Tables or Years

ADVANCED FILTER + CALCULATE PATTERNS

Multiple Filters in a Single CALCULATE
Using NOT, EXCEPT, INTERSECT inside CALCULATE
Combine CALCULATE with FILTER(), VALUES(), ALLSELECTED(), KEEPFILTERS()

RELATIONSHIP MODELING TECHNIQUES

Virtual Relationships using DAX (TREATAS, LOOKUPVALUE)
USERELATIONSHIP vs. CROSSFILTER
Handling Bi-Directional Relationships with Care
Many-to-Many Solutions using DAX with Bridge Tables

PERFORMANCE OPTIMIZATION

Understanding and Using DAX Studio and VertiPaq Analyzer
Optimizing Calculated Columns vs. Measures
Query Plans and Storage Engine vs. Formula Engine
Cardinality and its impact on performance
Avoiding common DAX performance anti-patterns (e.g., misuse of SUMX inside FILTER)

DEBUGGING AND TESTING

Using DEFINE MEASURE and EVALUATE in DAX Studio
Evaluating DAX logic step-by-step with VAR and RETURN
Tools: Performance Analyzer in Power BI

SPECIAL FUNCTIONS AND USE CASES

GENERATE(), GENERATEALL(), ADDCOLUMNS()
SUMMARIZE(), SUMMARIZECOLUMNS(), GROUPBY()
ISINSCOPE(), SELECTEDVALUE() vs VALUES()
RANKX(), TOPN(), PERCENTILEX.INC
CONTAINS(), LOOKUPVALUE(), RELATEDTABLE()

SQL Querying

Introduction to MS-SQL

Creating a Database
Understanding Tables and Creating Tables
Inserting, Updating and Deleting Data
Querying Data
Filtering Data
Grouping Data
Ordering Data
Column Aliases
Table Aliases

DDL INSIGHTS

CREATE TABLE
Dropping Objects
CREATE INDEX
TEMPORARY OBJECTS
Object Naming and Dependencies

SELECT STATEMENTS

Simple SELECTs
Calculated and Derived Fields
SELECT TOP / BOTTOM Records
Derived Tables
Joins
Predicates
Subqueries
Aggregate Functions
GROUP BY and HAVING
UNION
ORDER BY

SQL Programming

DDL INSIGHTS

CREATE TABLE
Dropping Objects
TEMPORARY OBJECTS
Object Naming and Dependencies

INTRODUCTION TO SQL PROGRAMMING (T-SQL)

What is T-SQL?
Differences between SQL Querying and SQL Programming
Benefits of procedural SQL
Use cases in reporting, automation, and ETL

VARIABLES AND CONTROL STRUCTURES

Declaring and Using Variables (DECLARE, SET)
Conditional Logic: IF…ELSE
Loops: WHILE, BREAK, CONTINUE
Error Handling: TRY…CATCH, THROW
GOTO statement (rare but useful for certain scenarios)

USER-DEFINED FUNCTIONS (UDFs)

Scalar-Valued Functions
Table-Valued Functions (Inline and Multi-statement)
Best practices for performance
Use in SELECT, WHERE, JOIN clauses

STORED PROCEDURES

Creating and Executing Stored Procedures
Input Parameters, Output Parameters
Reusability and Modularity
Nested Stored Procedures
Use in ETL and Reporting pipelines

TEMPORARY AND TABLE VARIABLES

Temporary Tables (#Temp, ##GlobalTemp)
Table Variables (DECLARE @TableVar TABLE)
Differences, Use Cases, and Scope
CTEs (Common Table Expressions)

CURSORS

Introduction to Cursors
Declaring and Using Cursors
Static vs Dynamic Cursors
Use Cases and Performance Considerations

DYNAMIC SQL

Constructing SQL Statements on the Fly
Executing with EXEC() and sp_executesql

TRANSACTIONS AND ERROR HANDLING

Introduction to Transactions
BEGIN TRAN, COMMIT, ROLLBACK
Nesting Transactions
Isolation Levels
Locking and Blocking

TRIGGERS

AFTER INSERT, AFTER UPDATE, AFTER DELETE
INSTEAD OF Triggers
Auditing Changes
Performance considerations

TESTING AND DEBUGGING

PRINT Statements
RAISERROR for debugging
SQL Server Profiler / Extended Events (if applicable)
Debugging in SQL Server Management Studio (SSMS)

Microsoft Fabric and Power BI Ecosystem

Introduction to Microsoft Fabric architecture and vision
Understanding the unified platform concept of Fabric
Overview of Fabric modules: Lakehouse, Warehouse, Real-Time Analytics, Data Activator, Data Science
Exploring OneLake as the single data lake for all workloads
Introduction to DirectLake and how it changes Power BI performance
Power BI's deep integration into the Fabric platform
Comparison of Fabric with legacy tools (Synapse, Dataflows, Data Factory)
Navigating Fabric workspaces, domains, and permissions
Understanding Fabric's role in end-to-end data lifecycle
Licensing structure and Fabric capacities
Fabric as an evolution of Azure Synapse and Power BI Premium
Cross-module data sharing within Fabric
Use of Notebooks and Spark runtime for data professionals
Understanding Fabric in the context of business intelligence
Connecting Power BI Desktop to Fabric datasets and models

Microsoft Fabric: Data Modeling with Fabric Lakehouse

Introduction to Lakehouse and its architecture
Differences between Lakehouse and traditional data lakes
Creating Lakehouse objects: managed vs unmanaged tables
Loading data using Dataflows Gen2 into Lakehouse
Delta Lake format and its benefits for performance and reliability
Schema management and table partitioning
Working with notebooks in Lakehouse for transformations
Using Spark to process and refine raw data
Connecting Power BI to Lakehouse via DirectLake
Creating semantic models from Lakehouse tables
Best practices for folder structures and naming conventions
Lakehouse security and access control in Fabric
Performance optimization for large data models in Lakehouse
Versioning and auditability in Lakehouse data
Integrating Lakehouse data into Power BI dashboards

Microsoft Fabric: Data Modeling with Fabric Data Warehouse

Introduction to the Fabric Data Warehouse module
Understanding structured modeling vs Lakehouse
Creating Warehouse tables, views, stored procedures
Building star schemas and dimensional models
Data ingestion into Warehouse using pipelines or Dataflows
Best practices for table relationships and indexing
Optimizing DAX performance on Warehouse models
Creating and querying views for report consumption
Understanding DirectQuery vs DirectLake vs Import modes
Connecting Power BI to Fabric Data Warehouse
Warehouse data governance and role-based access control
Integrating Warehouse and Lakehouse models in one dataset
Use cases for Warehouse vs Lakehouse
Monitoring and auditing Warehouse usage
Data lineage and impact analysis within Fabric Warehouse

Microsoft Fabric: Developing Reports and Dashboards Fabrics

Connecting Power BI to Lakehouse and Warehouse datasets
Building semantic models with measures, columns, hierarchies
Designing star schema datasets for optimal performance
Creating dynamic visuals: charts, tables, KPI cards
Using bookmarks, slicers, drillthrough, and tooltips
Creating interactive navigation experiences in Power BI
Implementing row-level and object-level security
Using custom visuals for advanced reporting needs
Formatting reports with branding and design standards
Designing mobile-friendly Power BI dashboards
Creating paginated reports for pixel-perfect outputs
Embedding reports in web apps or Teams environments
Using Q&A and AI visuals for smart exploration
Performance tuning with Aggregations and Composite Models
Publishing, sharing, and certifying reports within Fabric workspaces

Microsoft Fabric: Real-Time Analytics in Fabric

Introduction to KQL (Kusto Query Language)
Creating Real-Time Analytics databases in Fabric
Ingesting streaming data from multiple sources
Defining data ingestion policies for real-time datasets
Querying KQL databases from Power BI
Designing dashboards for real-time metrics
Use cases: IoT, web analytics, stock prices, sales live feed
Setting up alerts and thresholds with Data Activator
Comparing Real-Time Analytics with traditional BI
Managing ingestion latency and data freshness
Visualizing real-time vs near real-time data
Securing KQL datasets and managing access
Building composite models with real-time + historical data
Scaling real-time dashboards with large volume streams
Monitoring and logging for KQL and streaming performance

Microsoft Fabric: Advanced Topics

Power BI Governance in Fabric: certification, endorsement, monitoring
Deployment pipelines for Dev ➝ Test ➝ Prod
Workspace and artifact-level permission strategies
Advanced RLS and OLS implementations
Performance optimization with VertiPaq Analyzer and DAX Studio
Version control and change tracking in Fabric environments
Incremental refresh in DirectLake and hybrid models
Power BI Composite and Hybrid models explained
Creating semantic calculation groups and perspectives
Automating report workflows using Power Automate
Using Data Activator for rule-based triggers and alerts
Audit logging and activity monitoring in Fabric tenant
Capacity management and Fabric licensing optimization
Using Fabric with external tools: Excel, Azure Data Explorer, Synapse
Building reusable report templates and model layers for enterprise use

System Requirements

Power BI Desktop

Free & Downloadable from Microsoft Store App

https://www.microsoft.com/store/productid/9NTXR16HNW1T?ocid=pdpshare
Excel 2016 & above with PowerPivot

Available with Office 365 subscriptions that include desktop versions of Excel for Windows.
MS-SQL Server

https://www.microsoft.com/en-in/sql-server/sql-server-downloads

Kindly install Developer Edition as it is full-featured free edition, licensed for use as a development and test database in a non-production environment.
SQL Server Management Studio (SSMS)

Download and install SSMS from https://learn.microsoft.com/en-us/sql/ssms/download-sql-server-management-studio-ssms?view=sql-server-ver16
Secondary Monitor (optional, but recommended)

Having a secondary monitor will greatly assist in following the pace of the trainer. It allows you to view instructions and your own workspace simultaneously, enhancing your learning experience.

Taught by Microsoft Certified Trainers

All our classes are live,
hands-on and with
real-trainers.

Power BI & Fabric for Cloud Reporting

Real-World Projects. Enterprise Impact.

This course features hands-on projects modeled on real-world BI challenges in a cloud-first environment. You’ll work with OneLake, Lakehouses, and certified datasets—designing governed, scalable dashboards with Power BI. Master the tools to build enterprise-ready, collaborative reporting systems.

Power BI

SQL

Microsoft Fabric

Inventory & Supply Chain Dashboard

Create dynamic visualizations that track inventory levels, order fulfillment rates, and supplier performance. Learn to automate real-time data alerts to ensure optimal stock levels and timely deliveries.

Financial Health Dashboard

Build financial dashboards that display key metrics like revenue, expenses, and cash flow, with live updates. Automate reports that compare actual vs. budget figures and offer real-time insights for business decisions.

Customer Support Dashboard

Visualize customer service metrics such as ticket status, response times, and customer satisfaction. Learn how to automate ticket updates and generate insights to improve support efficiency.

Sales Performance Dashboard

Track sales revenue, regional performance, and top-selling products using dynamic visualizations. Create automatic reports to measure progress against sales targets.

Project Management Dashboard

Design a project management dashboard that tracks timelines, budgets, and milestones in real time. Automate status updates to identify risks or delays early.

Marketing Campaign Dashboard

Build dashboards that visualize key marketing metrics, such as conversions, impressions, and ROI. Automate reports to evaluate campaign success and optimize marketing strategies.

Database Design & Normalization

Design and normalize relational databases using primary keys,foreign keys, and normal forms to optimize storage and scalability.

Customer Data Analysis

Analyze customer data with JOINs, GROUP BY, and HAVING to identify trends, segment groups, and generate insights for marketing.

Sales Data Analysis

Use window functions and CTEs to track sales metrics, revenue, and product performance, generating actionable insights.

Inventory Management Queries

Leverage subqueries, UNION, and CASE to track inventory, product stock, and sales velocity for decision-making.

Employee Performance Tracker

Apply ranking functions (e.g., RANK(), DENSE_RANK()) to evaluate employee performance, track KPIs, and enhance workforce management.

Financial Reporting Queries

Retrieve financial data using aggregate functions and GROUP BY to automate real-time reports for balance sheets and P&L statements.

Sales & Forecasting with OneLake

Leverage Microsoft Fabric’s Lakehouse to build a Power BI dashboard that tracks regional sales, product performance, and forecast accuracy. Use certified datasets for consistency across business units.

Multi-Department Reporting Hub

Create a governed, cloud-based reporting system using Power BI and OneLake that brings together data from Finance, HR, and Operations. Implement workspace roles and row-level security to support cross-team collaboration.

Real-Time Logistics Monitoring

Build a live logistics dashboard by integrating Fabric Eventstreams (or real-time sources) with Power BI. Monitor delivery timelines, route efficiency, and exception alerts—all backed by structured Lakehouse data.

Enterprise KPIs on Fabric Lakehouse

Design a KPI monitoring system where business-critical metrics are standardized in the Lakehouse and consumed via Power BI. Use semantic models and centralized dataset management for version control and governance.

Cost Optimization & Usage Analytics

Analyze organizational data consumption and storage across Microsoft Fabric. Build Power BI dashboards that highlight dataset usage, refresh history, and storage costs—helping teams make cost-conscious data decisions.