Data Analysis And Business Intelligence With Sql And Python

Unlock the Power of SQL Server for Data Management, Data Analysis. Business Analyst, BI Developer and Database Developer

What you'll learn

Database Fundamentals

SQL Basics to Advance with Many use cases

SQL for Data Analyst, Business Analyst, BI Developer

SQL Programming (Function, Procedure, Trigger, Cursor)

SQL use cases to crack certification exam

Interview preparation with Multiple Solved Questions

Requirements

No Programming experience needed. You will learn everything you need to know

Description

The “Data Analysis and Business Intelligence with SQL and Python” course is designed to equip learners with the essential skills required to analyze, interpret, and visualize data for effective business decision-making. This program blends the power of SQL for data querying and management with the flexibility of Python for advanced analytics and automation, making it ideal for professionals aiming to build a career in data analysis, business intelligence, or data-driven roles.The course begins with a strong foundation in SQL, teaching participants how to design queries, join datasets, aggregate results, and manage databases efficiently. Learners will practice extracting actionable insights from large datasets and creating optimized queries suitable for real-world business applications.Building on this foundation, the program introduces Python for Data Analysis, covering libraries such as Pandas, NumPy, and Matplotlib. Participants will learn to clean, transform, and analyze data, as well as build visualizations that communicate trends and patterns effectively. Practical case studies and projects integrate SQL and Python, demonstrating how both tools complement each other in solving business problems.By the end of the course, learners will be able to handle end-to-end data analysis workflows—from extracting and preparing data to generating dashboards and reports that support strategic business decisions. This course is highly suited for working professionals, business analysts, and aspiring data scientists seeking to upskill in business intelligence and analytics.

Overview

Section 1: INTRODUCTION

Lecture 1 Introduction to SQL Server

Lecture 2 Installation of SQL Server

Lecture 3 Practice Dataset and PPT

Lecture 4 RDBMS

Lecture 5 Server and Database

Lecture 6 Data vs Information

Lecture 7 Table, Record and Field

Section 2: DATABASE

Lecture 8 Create Database

Lecture 9 Activate Database

Lecture 10 Drop Database

Section 3: TABLE

Lecture 11 Create Table

Lecture 12 Temporary Table (Local and Global)

Lecture 13 Delete Table or Drop Table

Section 4: DATA

Lecture 14 Insert Data into Table

Lecture 15 Insert Data with Graphical User Interface

Lecture 16 Import Data from External Source

Lecture 17 Export Data into External Source

Lecture 18 Database Backup

Section 5: SQL DATA TYPE

Lecture 19 String Data Type

Lecture 20 Number Data Type

Lecture 21 Date Data Type

Section 6: CONSTRAINTS

Lecture 22 Not Null to Prevent Null in Field

Lecture 23 Unique Key for Unique Data

Lecture 24 Primary Key with Live Scenario

Lecture 25 Foreign Key with Live Scenario

Lecture 26 Check for Specific Data in Field

Lecture 27 Default for Fix Value Instead of Null

Lecture 28 Identity for Auto Number

Section 7: SQL COMMAND TYPE

Lecture 29 Introduction to Command Type in SQL

Lecture 30 DQL Command with Live Scenario

Lecture 31 DDL Command with Live Scenario

Lecture 32 DML Command with Live Scenario

Section 8: INSERT STATEMENT

Lecture 33 INSERT Single Data

Lecture 34 INSERT Multiple Data

Lecture 35 INSERT Data in Selected Fields

Lecture 36 INSERT Data from One Table to Another Table

Lecture 37 INSERT Data from One Database Table to Another Database Table

Lecture 38 BULK INSERT data into Table

Section 9: FILTER DATA with WHERE CLAUSE

Lecture 39 Introduction of Where

Lecture 40 Apply Single Condition

Lecture 41 Apply Multiple Conditions

Section 10: SELECT STATEMENT with OPERATORS

Lecture 42 Introduction to Select Statement

Lecture 43 AND Operator

Lecture 44 OR Operator

Lecture 45 TOP and Bottom N Number of Records

Lecture 46 IN Operator with Live Scenario

Lecture 47 BETWEEN Operator with Live Scenario

Lecture 48 LIKE Operator with Live Scenario

Lecture 49 IS NULL with Live Scenario

Lecture 50 IS NOT NULL with Live Scenario

Lecture 51 EXISTS Operator

Lecture 52 NOT EXISTS Operator

Section 11: UPDATE STATEMENT with OPERATORS

Lecture 53 Introduction to Update Statement

Lecture 54 Update on Multiple Scenarios

Lecture 55 Update One Data in Entire Column and Salary Increment

Lecture 56 Update Multiple Fields Data

Lecture 57 Update One Table from Another Table Data

Section 12: DELETE with OPERATORS

Lecture 58 Introduction to Delete

Lecture 59 Delete, Truncate and Drop

Lecture 60 Delete Specific Data

Lecture 61 Delete Entire Data from Table

Lecture 62 Delete Data on Multiple Conditions

Lecture 63 Delete Data from One Table to Another Table with IN Operator

Lecture 64 Delete Data from One Table to Another Table with EXISTS Operator

Lecture 65 Delete vs Truncate

Section 13: GROUP BY and HAVING with Multiple Use Case

Lecture 66 Group Data on Single Field

Lecture 67 Group and Aggregate Data on Single Field

Lecture 68 Group by on Single Field with Multiple Aggregations

Lecture 69 Group Data on Multiple Fields

Lecture 70 Group by and Aggregation with Multiple Fields

Lecture 71 Department Base Contribution of Grand Total Salary

Lecture 72 Condition with Having Clause

Lecture 73 Where vs Having Clause

Lecture 74 Group by on Multiple Fields with Having for Condition

Lecture 75 Sequence of Group by, Having, Where and Order by

Lecture 76 Extract Duplicate and Unique Data Using Having Clause

Section 14: UNIQUE DATA EXTRACTION

Lecture 77 Distinct on Single Field

Lecture 78 Distinct Data with Group by

Lecture 79 Distinct on Multiple Fields

Lecture 80 Distinct on Multiple Fields with Group by

Section 15: ORDER BY TO SORT DATA

Lecture 81 Sort Data in Ascending or Descending Order on Single Field

Lecture 82 Sort and Filter Data in Ascending Orders

Lecture 83 Sort and Filter Data in Descending Orders

Lecture 84 Sort Data in Ascending or Descending Order on Multiple Fields

Lecture 85 Group Field and Sort Data in Ascending or Descending Order

Section 16: SUB QUERY

Lecture 86 Extract Data of Max Value

Lecture 87 Extract Data of Min Value

Lecture 88 Extract Data of More than Average

Lecture 89 Compare Two Tables Data and Extract Matching Data

Lecture 90 Extract Data of 3rd Largest Value

Lecture 91 Extract Data of 3rd Smallest Value

Lecture 92 Extract 3rd Largest Value of Grouped Data

Section 17: WINDOW FUNCTION

Lecture 93 Row_Number Function

Lecture 94 Rank Function

Lecture 95 Dense_Rank Function

Lecture 96 Basic Lead and Lag

Lecture 97 Lead and Lag on Date Field

Lecture 98 Yearly Sales Comparison with Lead and Lag

Lecture 99 Lead and Lag with Partition by

Lecture 100 Cumulative Total

Lecture 101 Cumulative Total by Partition

Lecture 102 Moving Average

Section 18: CTE (COMMON TABLE EXPRESSION)

Lecture 103 CTE Introduction

Lecture 104 Extract Product Name of 3rd Lowest Sales

Lecture 105 Extract Product Name of 3rd Highest Sales

Lecture 106 Extract Two Ranked Values of Each Partition

Lecture 107 Delete Duplicate Excluding One

Section 19: CASE STATEMENT

Lecture 108 Create Conditional Fields

Section 20: SQL JOIN

Lecture 109 Introduction to Join

Lecture 110 Inner Join

Lecture 111 Left Join

Lecture 112 Left Anti Join (Not Matched Data)

Lecture 113 Right Join

Lecture 114 Right Anti Join (Not Matched Data)

Lecture 115 Full Join

Lecture 116 Cross Join

Lecture 117 Self Join

Section 21: APPEND WITH SET OPERATION

Lecture 118 Union with Live Scenario

Lecture 119 Union All with Live Scenario

Lecture 120 Intersect with Live Scenario

Lecture 121 Except with Live Scenario

Section 22: DATA BACKUP

Lecture 122 Select Into with Live Scenario

Lecture 123 Insert Into Select with Live Scenario

Section 23: SQL VIEW

Lecture 124 Introduction to View

Lecture 125 Create and Alter View

Lecture 126 Changes in View and Master Table

Section 24: INDEX

Lecture 127 Introduction to Index

Lecture 128 Create Clustered Index

Lecture 129 Create Non-Clustered Index

Section 25: ALTER

Lecture 130 Alter Table

Lecture 131 Alter View

Section 26: DROP

Lecture 132 Drop Database

Lecture 133 Drop Table

Lecture 134 Drop View

Lecture 135 Drop Index

Lecture 136 Drop Table Field

Section 27: FUNCTION

Lecture 137 SQL Aggregate Function

Lecture 138 SQL String Function

Lecture 139 SQL String Function Use Case

Lecture 140 Basic Date Function

Lecture 141 Datename and Datepart Function

Lecture 142 Dateadd Function

Lecture 143 Datediff Function

Lecture 144 Coalesce Function

Lecture 145 Data Type Change by Convert and Cast Functions

Section 28: Store Procedure

Lecture 146 Introduction of Store Procedure

Lecture 147 Basic Store Procedure

Lecture 148 Alter Store Procedure

Lecture 149 Create Parameterized Procedure

Lecture 150 Create Procedure to Update Staging Table

Section 29: Trigger

Lecture 151 Trigger for Insert, Update and Delete

Section 30: Python

Lecture 152 Python Introduction

Section 31: Python Basic

Lecture 153 Python Comments

Lecture 154 Python Shortcuts

Lecture 155 Python Markdown and Header Cell

Lecture 156 Python Code Navigation

Lecture 157 Python Indentation

Lecture 158 Python Basic Script

Lecture 159 Python Casting

Section 32: Operators and Operands

Lecture 160 Operator and Operand Introduction

Lecture 161 Python Basic Operators

Lecture 162 Python Arithmetic Operators

Lecture 163 Python Special Arithmetic Operator

Lecture 164 Python Arithmetic Calculation

Lecture 165 Python Operators (IN)

Lecture 166 Python Operators (IS)

Lecture 167 Python Operators (Single Input)

Lecture 168 Python Operators (Multiple Input)

Section 33: Python Variables

Lecture 169 Python Variable

Lecture 170 Python Local Variable

Lecture 171 Python Global Variable

Lecture 172 Python Multi Line Variables values

Section 34: Data Types

Lecture 173 Python Data Type Introduction

Lecture 174 Python Data Type Check Part 2

Lecture 175 Python Data Type Check (List, Tuple, Set, Dict)

Section 35: Data Type String Operations

Lecture 176 Python String Multi Line Values

Lecture 177 Python String Slicing

Lecture 178 Python String Modification

Lecture 179 Python Split Operation

Lecture 180 Python String and Number Concatenation

Lecture 181 Python String Formatting

Lecture 182 Python String Formatting Part 2

Section 36: Data Type List

Lecture 183 Python List Operation

Lecture 184 Python Operators (AND)

Lecture 185 Python List Check Value

Lecture 186 Python List Change

Lecture 187 Python Complete List Change

Lecture 188 Python List Extend and Append

Lecture 189 Python Clear List

Lecture 190 Python For Loop over List

Lecture 191 Python For Loop Over List for Text Analytics

Lecture 192 Python Sort Over List Value

Lecture 193 Python List Copy

Lecture 194 Python List Join

Section 37: Data Type Tuple

Lecture 195 Python Tuple Operation

Lecture 196 Python Tuple Access Data

Lecture 197 Python Tuple Update

Lecture 198 Python Unpack Tuple

Lecture 199 Python Tuple Join

Lecture 200 Python Tuple Method

Lecture 201 Python Tuple For Loop

Lecture 202 Python Tuple While Loop

Section 38: Data Type Set

Lecture 203 Python Basic Set

Lecture 204 Python Set Unique

Lecture 205 Python Add Method

Lecture 206 Python Update Method

Lecture 207 Python Remove Method

Lecture 208 Python Set Intersection and Difference

Lecture 209 Python Set Intersection and Intersection_update

Lecture 210 Python Set Difference, Symmetric_Difference and Difference_Update

Lecture 211 Python Set issubset, issuperset, isdisjoint

Lecture 212 Python Set Operators (Union, Intersection, Difference, Symmetric Difference)

Lecture 213 Python Set Operators (Subset, Superset, Equal, Not Equil)

Lecture 214 Python Set with Loop

Section 39: Data Type Dictionary

Lecture 215 Dictionary Introduction

Lecture 216 Dictionary Len and Type Function

Lecture 217 Dictionary Specific Key Output

Lecture 218 Convert Tuple to Disctionary Example1

Lecture 219 Convert Tuple to Dictionary Example2

Lecture 220 Convert Tuple to List to Dictionary

Lecture 221 Map Two Different Data Type Values with Zip Function

Lecture 222 Map Two Lists Values with Zip Function

Lecture 223 Modify Dictionary

Lecture 224 Copy Dictionary

Lecture 225 Nested Dictionary

Lecture 226 Dictionary with For Loop

Lecture 227 Dictionary with Logical Operator

Section 40: Loops

Lecture 228 For Loop Print Value

Lecture 229 For Loop Print value in reverse order

Lecture 230 For Loop Print value and complete

Lecture 231 Python Reverse Character and Number

This course is for them who want to mark career as a Data Analyst, Business Analyst, MIS Analyst and Database Developer