POWER BI Data Analyst Slider 1

#Data Analyst

Data Analyst is a promising job role that deals with Data, Analysis, Derived Information and drive to Infographics of enterprise content. This role also involves Data collection, data processing, and data analysis to identify trends, patterns, and relationships that can be used to solve problems and make informed decisions with ease !

Training Highlights

✅ SQL for Data Analysis & Reporting
✅ Advanced Excel, Pivot Tables, Dashboards
✅ Power BI for Interactive Visualizations
✅ Data Cleaning with Power Query
✅ Python: Pandas, NumPy, Visualization
✅ Statistics, Exploratory Data Analysis (EDA)
✅ Business Intelligence & Storytelling
✅ Real-Time Projects with Case Studies
✅ Resume Building, Portfolio & GitHub Profile
✅ 1:1 Mentorship & Interview Preparation

Modules We Learn

✅ Module 1: MSSQL, TSQL & Tuning
✅ Module 2: Power BI with AI
✅ Module 3: Python Analytics
✅ Module 4: Advanced Excel
✅ Module 5: Two Realtime Projects

Course Duration: 3 Months

Power BI analytics banner showing data-driven decision making with interactive dashboards and business intelligence reporting

Data Analyst
Course Contents:

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Module 1: MSSQL & TSQL

Ch 1: SQL Database Job Roles

Database Intro
OLTP, DWH, OLAP
DBMS Basics
Data Analyst Job Roles

Ch 2: Database Intro & Installations

SQL Server Installations
Instance & Collations
SSMS Tool Installation
Connections, Authentications

Ch 3: SQL Basics V1 (Commands)

SQL Basics (DDL, DML, etc..)
Creating Databases, Tables
Data Inserts (GUI, SQL)
Basic SELECT Queries

Ch 4: SQL Basics V2 (Commands, Operators)

DDL: Create, Alter, Drop
DML: Insert, Update, Delete
DQL: Select, Fetch
Add, Truncate Statements
SQL Operators

Ch 5: Data Types & Variables

Integer Data Types
Character, MAX Data Types
Decimal & Boolean Data Types
Date and Time Data Types
SQL_Variant Type

Ch 6: Data Imports

Data Imports with Excel
Data Imports with CSV
Data Types Detection
OLE-DB Connections
ORDER BY, TOP, OFFSET

Ch 7: Schemas & Batches

Schemas & Table Grouping
Real-world Banking Database
2 Part, 3 Part & 4 Part Naming
Batch Concept & “Go” Command

Ch 8: Constraints, Keys & RDBMS

Null, Not Null Constraints
Unique Key & Check
Primary Key Constraint
Foreign Keys, Default
DB Diagrams & ER Models

Ch 9: Normal Forms & RDBMS

Normal Forms: 1 NF, 2 NF
3 NF, BCNF and 4 NF
1:1, 1:M, M:1 Cardinality
Cascading Keys, Self Referencing Keys

Ch 10: Joins & Queries

Joins: Table Comparisons
Inner Joins & Matching Data
Outer Joins: LEFT, RIGHT
Full Outer Joins & Aliases
Self Joins & Aliases

Ch 11: Sub Queries

Basic Sub Queries
Aggregations
Combining Queries
Correlated Sub Queries
UNION, UNION ALL

Ch 12: Group By Queries

Group By, Distinct
GROUP BY, HAVING
Cube( ) and Rollup( )
Sub Totals & Grand Totals
Grouping( ) & Usage
ISNULL, COALESCE

Ch 13: Joins with Group By, Sub Queries

3 Table, 4 Table Joins
Join Queries & WHERE
Join & Group By, Sub Queries
IIF(), CASE Statement
EXISTS, NOT EXISTS
Query Execution Order

Ch 14: Views & RLS

Views: Realtime Usage
DML, SELECT with Views
WITH CHECK OPTION
Row Level Security (RLS)
Important System Views

Ch 15: Functions & Queries

User Defined Functions
Scalar, Table Value Functions
Variables & Parameters
Date & Time Functions
String Functions
Aggregated Functions
Data Conversion Functions

Ch 16: Advanced SQL & Window Functions

Window Functions (Rank)
Row_Number, DenseRank
Partition By & Order By
Lag & Lead Functions
Pivot, UnPivot
Running Totals
Moving Average

Ch 17: Stored Procedures – 1

Stored Procedures: Realtime Use
Parameters Concept with SPs
Procedures with SELECT
System Stored Procedures
Stored Procedures, Tuning

Ch 18: Stored Procedures – 2

Merge Statement (Upsert)
Merge with OLTP & DWH
Matched and Not Matched
Merge & SP Recompilations

Ch 19: Triggers & Automations

Need for Triggers in Real-world
DDL & DML Triggers
For / After Triggers
Instead Of Triggers
Disabling DMLs Triggers

Ch 20: Transactions & ACID

Auto Commit Transaction
Explicit Transactions
COMMIT, ROLLBACK
Checkpoint & Query Blocking
READPAST, LOCKHINT
TRY…CATCH & Error Handling

Ch 21: SQL Query Performance & Indexing

Clustered vs Nonclustered Indexes
Index Seek vs Scan
Execution Plans
SARGable Queries
Tuning Queries
Avoiding SELECT *
Indexing JOIN/WHERE columns
Statistics Basics
Query Optimization Examples

Ch 22: CTEs & Tuning

Common Table Expression
CTEs for Data Retrieval
CTEs for DML Operations
Data Cleansing Techniques
Duplicate Detection/Removal

Ch 23: Temp Tables & Query Techniques

Local & Global Temp Tables
SELECT..INTO Statement
Cursor Basics – When to Use & Avoid
NULLIF
Basic Execution-Plan Reading

Ch 24: Bonus / Advanced Module: SQL Server Internals

Database Engine Components
Parser, Compiler & Optimizer
Parsing and Compilation
Memory Manager & IO Managers

Real-Time Project on HealthCare Domain
Project Requirement:
Solve 20+ Real-World Healthcare Business Requirements.

Project Workflow:
Database Design → SQL Development → Data Analysis → Performance Optimization

Project Operational Flow:
Healthcare DB → Patients → Doctors → Appointments → Treatments → Billing → Insurance → SQL
Analysis → Stored Procedures → Performance Tuning → Business Reports
www.sqlschool.com For Free Demo: Reach us on +91 9666 44 0801 or +91 9666 64 0801

Business Requirements:
Monthly Hospital Revenue, Top Doctors By Patients Treated, Repeat Patients, Department
Performance, Average Treatment Cost, Unpaid Bills, Insurance Claim Analysis, Patient Trends,
Month-Over-Month Revenue And Top Procedures…

Module 2: Power BI

Ch 1: Power BI Intro, Installation

Power BI & Data Analysis
Power BI Eco System
Power BI Design Tools
Power BI Installation

Ch 2: Report Design Concepts

Basic Report Design (PBIX)
Data Points, Spotlight
Visual Interactions & Edits
Focus Mode, PDF Exports

Ch 3: Grouping, Hierarchies

Creating Groups: Lists
Creating Groups: Bins
Hierarchies & Drill-Downs
Drill Up, Conditional DrillDown

Ch 4: Slicer & Visual Sync

Slicer Visual in Power BI
Slicer: Format Options
Single Select, Multi Select
Slicer: Select All On / Off
Visual Sync with Slicers

Ch 5: Filters & Drill Thru

Power BI Filters
Basic, Top & Advanced
Visual Filters, Page Filters
Report Level Filters, Clear Filter
Drill Thru Filters & Usage

Ch 6: Bookmarks, Buttons

Power BI Bookmarks
Images: Actions, Bookmarks
Buttons: Actions, Bookmarks
Page to Page Navigations
Score Cards, Master Pages

Ch 7: SQL DB Access & Big Data

SQL DB Access, Queries
Storage Modes: Direct Query
Formatting & Date Time
Storage Modes in Power BI
Data Modeling & Formatting

Ch 8: Power BI Visualizations

Charts, Bars, Lines, Area
Tree Maps & Axis Items
Funnel, Card, Mult-Row Card
Pie Charts & Waterfall
Scatter Chart, Play Axis
Infographics, Classifications

Ch 9: Power Query Transformations – 1

Power Query (Mashup)
ETL Transformations in PBI
Table Combine Options
Merge, Union All Options
Missing Values, Duplicate Records
Wrong Data Types, Outliers
Close, Apply & Visualize

Ch 10: Power Query Transformations – 2

Group By Transformation
Aggregate, Pivot Operation
Reverse Rows, Count Rows
Data Cleaning, Null Handling
Data Type Detection, Change
Rename, Replace, Move
Fill Up, Fil Down

Ch 11: Power Query Transformations – 3

String / Text Transformations
Split, Merge, Extract, Format
Numeric and Date Time
Add Column & Expressions
Column From Examples

Ch 12: Power Query Transformations – 4

Parameters in Power Query
Static Parameters, Defaults
Dynamic Dropdowns, Lists
Linking with Table Queries
Step Edits, Type Conversions

Ch 13: Power BI Cloud & Fabric

Power BI Cloud, Microsoft Fabric
Microsoft Fabric Concepts
Fabric One Lake (DWH, LH, etc.)
Microsoft Fabric Workspace
Power BI Desktop Connections
Report Uploads (PBIX)
Report Edits, Semantic Models

Ch 14: Power BI Cloud Dashboards

Power BI Dashboards
Dashboard Creation, Usage
Pin Visuals, Pin LIVE Pages
Add Image, Video Tiles
Q&A & Pin Tiles

Ch 15: Power BI Cloud Operations

Report Shares, Alerts
Subscriptions, Exploration
Downloads & Edits
Report Cloning in Cloud
QR Codes, Web Publish
Lineage & Metrics

Ch 16: Power BI Cloud Gateways

Data Gateways, Data Refresh
Install, Configure Gateways
Data Refresh & Scheduling
Gateway Optimizations
Incremental Refresh
Large Dataset Optimization

Ch 17: Power BI Cloud Apps

Power BI Apps: Creation
App Sections & Content
Audience & App Security
App Updates, Favorites
App URL, End User Access

Ch 18: Power BI Report Server, RDL

Power BI Report Server
RS Config Tool Options
Report Database, TempDB
Web Service & Server URL
Report Builder Tool
Paginated Report (RDL)
RDL Report Publish

Ch 19: DAX Concepts & Calculations

DAX Concepts: Intro & Realtime Need
DAX Columns: Creation, Use
DAX Measures: Creation, Use
DAX Functions: IIF, ISBLANK
SUM, CALCULATE Functions

Ch 20: DAX Quick Measures

Quick Measures in Power BI
Running Totals
Star Rating Calculations
DAX Measures in Data View
DAX in Cloud Reports

Ch 21: Data Modelling

Dimensions Tables
Fact Tables & DAX Measures
Data Models & DDAX Joins
Star & Snowflake Schemas
Many-to-Many Relationships
Calculation Groups

Ch 22: DAX Joins, Variables

CALCULATEX & Variables
COUNT, COUNTA, etc..
SUM, SUMX, etc..
SELECTED MEMEBER
Filter Context, RETURN

Ch 23: DAX Models & Calculations

VAR, SWITCH, SUMMARIZE
TREATAS, USERELATIONSHIP
CROSSFILTER, GENERATE
RANKX, TOPN, WINDOW
OFFSET, INDEX

Ch 24: DAX Time Intelligence

Need for Time Intelligence
Date Table Generation
Time Intelligence with DAX
PARALLELPERIOD, DATE
CALENDAR, Total Functions
YTD, QTD, MTD with DAX

Ch 25: DAX – Row Level Security

RLS: Row Level Security
Data Modelling & Roles
Add Cloud Users & KPIs
CoPilot with DAX

Ch 26: DAX – Analytical Reports

DAX with Excel
Analytical Reports
Virtual Cube Concepts
Cross Filter Reporting
Alerts, Data Activator

Ch 27: PL 300 Exam Guidance

PL 300 Exam Guidance
Exam Samples
Exam Scenarios

Realtime Project: Enterprise Healthcare Data & Analytics Platform
Project Objective
Design and implement a modern Healthcare Data Platform using Power BI Analytics and Reporting services
to process patient, hospital, clinical, and operational data for reporting, analytics, and decision-making.
Technologies Used

SQL Server
MS Excel
Parquet
CSV
PDF
Azure

Learning Outcomes
After completing this project, you can confidently showcase experience in:

Power BI Reporting
Power BI Data Analytics
Business Process Understanding
Performance Optimization
End-to-End Power BI Implementation in Cloud

Module 3: Python (For Data Analysts)

Ch 1: Python Introduction

Python Introduction
Python Versions
Python for Data Analysts
Python Architecture

Ch 2: Python Installations

Python Introduction
Python Installations
Anaconda Installation
Python IDE & Usage
Jupyter Notebooks

Ch 3: Python Print Statement

Python Print Statement
print(), print()
Testing Case Sensitivity
Single Line, Multi Line prints
print() with single quotations
Debug with AI (AI Assistants)

Ch 4: Python Variables

Python Variables
Assigning values
Variable Value Reads
Multiple Variables & Print()

Ch 5: Python Operators

Athematic Operators
Python String Literals
Single, Double Quotes
Format Strings (f string)
Comparison, Indexing Operators

Ch 6: Python Data Types

Python Data Types
Integer, Float, String Data Types
Type Casting
Type Identification
Multi Value Assignments

Ch 7: Python Lists

Creating Python Lists
Printing List Items
Print List Slices
Empty Lists, Append
Loops, List Updates

Ch 8: Python Dictionaries

Python Dictionary
Indexing Dictionaries
Edit Key Values
Lists inside Dictionaries
Delete & Clear

Ch 9: Python Tuples

Python Tuples
Defining, Indexing
Length(), Type()
Mixed Values in Tuples
Overwriting Tuples

Ch 10: Python IF..ELSE Condition

If..Else conditions
if..elif..else & Shorthand if
composite conditions
Indent, pass statement
in & negation operators
range conditions

Ch 11: Python Loops

Python For Loop
For Loop @ Range
For Loop @ Sequence Values
While Loop, Exit Conditions
Nested Loops
Break, Continue, Paas

Ch 12: Python Dataframes

Dataframes: Creation
Pandas Dataframes
Dataframes From Single List
Dataframes from Dictionary
Display Dataframes, List Items
Identify, Replace Nulls, NumPy

Ch 13: Python SQL DB Access

SQL DB Access with Python
import pandas.DataFrame
pyodbc module, sql functions
SQL Query Executions: DDL, DML
Filters, Aggregations with SQL
Dataframe Usage with SQL

Ch 14: Dataframe Transformations – 1

Dataframe Transformations
Concat & Append
Merge Function
Join with Multiple Dataframes
Data Type Checks, Conversions
Loops with Dataframes

Ch 15: Dataframe Transformations – 2

Pandas – Cleaning Data
Replace, Transform Columns
Data Discovery & Column Fill
Identify & Remove Duplicates
dropna(), fillna() Functions

Ch 16: Dataframe Transformations – 3

Python Functions for date, time
Now() Function in Python
date, time Functions
Calendar Data Generation

Ch 17: Python Functions & Lambda

Python Functions & Usage
Function Parameters
Default & List Parameters
Python Lambda Functions
Recursive Functions, Usage
Return & Print @ Lamdba

Module 4: Excel Analytics (Basic to Advanced)

Ch 1: Excel Concepts, Basic Functions

Excel Basics & Concepts
Excel Functions
Excel Operations

Ch 2: Formatting and Proofing

Currency Format
Format Painter
Formatting Dates
Custom and Special Formats
Formatting Cells
Absolute, Mixed
Relative Referencing

Ch 3: Functions

SUMIF, SUMIFS, COUNTIF
COUNTIFS, AVERAGEIF
AVERAGEIFS, NESTED IF
IFERROR STATEMENT
AND, OR, NOT

Ch 4: Protecting Excel

File Level Protection
Workbook
Worksheet Protection
Security Concepts
Realtime Issues, Solutions

Ch 5: Text Functions

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

Ch 6: Date & Time Functions

Today, Now
Day, Month, Year
Date, Date if, Date Add
EOMONTH
Weekday Functions

Ch 7: Adv. Techniques

Paste Formulas
Paste Formats
Paste Validations
Transpose Tables

Ch 8: New in Excel & 365

Charts – Tree map & Waterfall
Sunburst, Box and whisker Charts
Combo Charts – Secondary Axis
Adding Slicers Tool in Pivot & Tables
Using Power Map and Power View
Forecast Sheet, park lines

Ch 9: New in Excel & 365

Using 3-D Map
New Controls in Pivot Table
Various Time Lines
Auto complete a data range
Quick Analysis Tool
Smart Lookup manage Store

Ch 10: Printing Workbooks

Setting Up Print Area
Customizing Headers
Templates
Print Titles –Repeat Rows

Ch 11: Sorting and Filtering

Filtering on Text
Numbers & Colors
Sorting Options
Advanced Filters
Filter Criteria

Ch 12: What If Analysis

Goal Seek
Scenario Analysis
Data Tables (PMT Function)
Solver Tool

Ch 13: Logical Functions

If Function
How to Fix Errors – if error
Nested If
Complex if and or functions

Ch 14: Data Validation

Number, Date & Time
Text and List Validation
Custom validations formulas
Dynamic Dropdowns

Ch 15: Lookup Functions

V lookup / H Lookup
Index and Match
Smooth User Interface
Nested V Lookup
Reverse Lookup
Worksheet linking
V lookup with Helper Column

Ch 16: Pivot Tables – 1

Creating Simple Pivot Tables
Classic Pivot table
Choosing Field
Filtering PivotTables
Modifying PivotTable Data
Grouping
Calculated Fields

Ch 17: Pivot Tables – 2

Array with IF, LEN
MID function formulas.
Array with Lookup functions.
Various Charts
SLICERS, Filter data
Manage Primary Axis
Manage Secondary Axis

Ch 18: Excel Dashboard

Planning a Dashboard
Adding Tables and Charts to Dashboard
Adding Dynamic Contents to Dashboard

Ch 19: VBA Macro – Level 1

Using Outlook Namespace
Send automated mail
Outlook Configurations, MAPI
Worksheet Operations
Workbook Operations

Ch 20: VBA Macro – Level 2

Merge Worksheets using Macro
Merge multiple excel files into one sheet
Split worksheets using VBA
Worksheet copiers

Ch 21: Statistics For Data Analysis – 1

Mean, Median
Mode, Variance
Standard Deviation
Correlation

Ch 22: Statistics For Data Analysis – 2

Probability Basics
Hypothesis Testing
A/B Testing
Confidence Interval
Outliers, Normal Distribution

Module 5: Realtime Projects

Realtime Project 1 (Ecommerce Domain)

Project Requirement
Project Solution
Project FAQs
AI Sales Dashboard

Realtime Project 2 (Finance Domain)

Project Requirement
Project Solution
Project FAQs
AI Financial Forecast

Career Guidance

Resume Optimization
LinkedIn Optimization
ATS-Friendly Resume
Interview Strategy

What is the Data Analyst course?

This program trains you to analyze data, build dashboards, use AI tools, write SQL queries, perform ETL, design Power BI reports, and apply Python for data analytics. It is fully job-oriented with 100% hands-on practice.

Who should join this Data Analyst course?

Anyone — freshers, non-IT learners, working professionals, and career switchers. The course starts from basics of data, databases, SQL, analysis, and reporting. No prior technical experience is required.

What are the modules included in this training?

Module 1: MSSQL & TSQL (3 Weeks, 2 Case Studies)
Module 2: Power BI with AI & CoPilot (4 Weeks, 4 Case Studies)
Module 3: Python for Data Analytics (3 Weeks, 1 Case Study)
Module 4: Realtime Projects + Excel + PL-300 + 1:1 Resume + Mock Interviews

SQL SCHOOL vs Other Institutes

SQL SCHOOL vs Other Institute Comparistion image

Training Modes

LIVE Online Training

Instructor Led

Self Paced Videos

On-Demand

Corporate Training

With 100% Hands-On

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

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Realtime Project FAQs
Course Completion Certificate
Placement Assistance
Job Support
Realtime Project Solution
MS Certification Guidance

SQL School Power BI Data Analyst training certificate of completion issued in January 2026 with verification ID