power-bi-sql-course-usa

From Power BI Basics to SQL-Driven Analytics

Power BI + SQL = Data Reporting Made Faster
Learn to connect, query, and create advanced reports.

Perfect for Power Users who want to "take Power BI to the next level." To learn Advanced DAX, understanding SQL is essential. This course builds on Power BI fundamentals and introduces SQL, enabling you to perform complex calculations, optimize reporting, and automate workflows—"without any coding experience."

Tools You'll Master in Power BI Training

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 3 Weeks with Power BI Training

Master SQL for Data Integration – Query and manage large datasets efficiently.

Take DAX to the Next Level – Create sophisticated measures for deeper analytics.

Optimize Data Models for Speed – Ensure smooth, high-performance reporting.

Automate Reports & Workflows – Reduce manual effort using SQL and DAX.

Handle Large Datasets with Ease – Work with SQL, Excel, and multiple data sources

Deliver Faster Insights – Optimize Power BI reports for real-time decision-making.

What You’ll Achieve in Just 3 Weeks with Power BI Training

Master SQL for Data Integration – Query and manage large datasets efficiently.

Take DAX to the Next Level – Create sophisticated measures for deeper analytics.

Optimize Data Models for Speed – Ensure smooth, high-performance reporting.

Automate Reports & Workflows – Reduce manual effort using SQL and DAX.

Handle Large Datasets with Ease – Work with SQL, Excel, and multiple data sources

Deliver Faster Insights – Optimize Power BI reports for real-time decision-making.

Ideal For:

Finance & Operations Professionals

who need SQL-powered analytics for forecasting and trend analysis.

Reporting Professionals

who need to connect databases with Power BI for dynamic reporting

Data Analysts

looking to combine SQL skills with Power BI for more advanced reporting.

Business Analysts

who want to bridge the gap between SQL databases and business reports.

BI Developers & IT Professionals

aiming to optimize data models and improve Power BI performance.

Non-technical professionals

with basic SQL knowledge, ready to build more complex reports with Power BI.

A snapshot of what you'll be learning in 3-weeks.

Course Syllabus Overview

Quick Excel Formulas Brush-up

Fundamentals Of Functions & Formulas Quick techniques to work with formulas & functions DATE AND TIME FUNCTIONS For data and time calculations

Today, Now
Day, Month, Year
Date, DateDif, DateAdd
EOMonth, Weekday
Workdays, NetWorkdays, Edate

TEXT FUNCTIONS For data transformations

Upper, Lower, Proper
Left, Mid, Right
Trim, Len
Concatenate
Find, Substitute

LOGICAL FUNCTIONS For conditional statement development

Nested If ( And Conditions , Or Conditions )
Alternative Solutions for Complex IF Conditions to make work simple
And, Or, Not

MATHEMATICAL FUNCTIONS For fundamental analysis

Sum, Count, CountA, Average, AverageA, Max & Min
SumIf, SumIfs
CountIf, CountIfs
AverageIf, AverageIfs
MaxIfs, MinIFs

LOOKUP FUNCTIONS For joins with multiple tables

Vlookup / HLookup
Match
Dynamic Two Way Lookup
Creating Smooth User Interface Using Lookup
Offset
Index
Dynamic Worksheet linking using Indirect

ERROR HANDLING FUNCTIONS For handling errors in functions

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)

Power BI 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.

Master Power BI Dashboards and SQL for Data Analytics

Real-time Projects (Practical Application)

This Power BI with SQL course includes 14 Power BI projects and 6 SQL projects, combining data visualization, data transformation, and SQL query skills. You’ll create interactive dashboards, transform data with Power Query, write DAX formulas, and master SQL queries. Here are the top Power BI and SQL projects you'll work on:

Power BI

SQL

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.