DEV Community: Punitha

SQL Setup and Installation

Punitha — Wed, 22 Jul 2026 02:16:36 +0000

Step 1: Download PostgreSQL

Visit the PostgreSQL official website
Download the latest PostgreSQL version compatible with your operating system
Run the installer

Step 2: Install PostgreSQL

Launch the installer
Click Next
Select the installation directory
Keep default components selected:
PostgreSQL Server
pgAdmin 4
Command Line Tools
Click Next

Step 3: Set Password

Enter a password for the postgres user
Confirm the password
Click Next

Step 4: Configure Port Number

Default Port: 5432
Click Next

Step 5: Complete Installation

Review settings
Click Install
Wait for installation to finish
Click Finish

Step 6: Open pgAdmin 4

Search for pgAdmin 4 in Windows
Open pgAdmin
Enter the password if prompted

Step 7: Connect to PostgreSQL Server

Expand Servers
Select PostgreSQL Server
Enter the password created during installation

Step 8: Create a New Database

Right-click Databases
Select Create -> Database
Enter database name
Click Save

Step 9: Open Query Tool

Select the database
Click Tools -> Query Tool

Step 10: Test SQL Query

SELECT 'Hello SQL';

Click Execute

IPL Match Analysis Dashboard

Punitha — Tue, 21 Jul 2026 03:01:49 +0000

Step 1: Import the Dataset

Open Power BI Desktop
Click Get Data
Select the IPL dataset(CSV/Excel)
Click Load

Step 2: Data Cleaning using Power Query Editor

Click Transform Data
Verify data types
Remove duplicate records
Handle missing values
Rename column names
Remove unnecessary columns
Click Close & Apply

Step 3: Create DAX Measures

Total Matches

Total Matches = COUNT(Cricket_data[id])

Total Runs

Total Runs = SUM(Cricket_data[home_runs]) + SUM(Cricket_data[away_runs])

Total Wickets

Total Wickets = SUM(Cricket_data[home_wickets]) + SUM(Cricket_data[away_wickets])

Total Boundaries

Total Boundaries = SUM(Cricket_data[home_boundaries]) + SUM(Cricket_data[away_boundaries])

Total Venues

Total Venues = DISTINCTCOUNT(Cricket_data[venue_name])

Step 4: Create Slicers

Season Slicer

Field: Season

Venue Slicer

Field: VenueName

Home Team Slicer

Field: HomeTeam

Step 5: Create KPI Cards

Card 1 - Total Matches

Card 2 - Total Runs

Card 3 - Total Wickets

Card 4 - Total Boundaries

Card 5 - Total Venues

Step 6: Create Matches by Season Chart

Select Column Chart
Drag Season -> Axis
Drag Match Count -> Values

Step 7: Create Winner Distribution Chart

Select Donut Chart
Drag Winner -> Legend
Drag Values -> Match Count

Step 8: Create Wickets by Team Chart

Select Column Chart
Drag Bowling Team -> Axis
Drag Total Wickets -> Values

Step 9: Create Team Wise Wins Chart

Select Bar Chart
Drag Winner -> Axis
Drag Values -> Values

Step 10: Create Decision Distribution

Select Donut Chart
Drag Decision -> Legend
Count of Matches -> Values

Step 11: Create Runs by Team Chart

Select Column Chart
Drag Batting Team -> Axis
Drag Total Runs -> Values

Step 12: Create Venue Wise Matches Chart

Select Bar Chart
Drag Venue Name -> Axis
Drag Match Count -> Count

Step 13: Create Super Over Analysis

Select Donut Chart
Drag Super Over -> Axis
Drag Match Count -> Values

Step 14: Create Toss Decision vs match Won Chart

Select Column Chart
Drag Decision -> Axis
Drag Matches Won -> Values

Step 15: Dashboard Formatting

IPL stadium background image
Consistent color theme
Card icons for KPIs
Borders around visuals
Data labels enabled
Titles added for all visuals

Portfolio Website CSS Page

Punitha — Mon, 20 Jul 2026 04:10:28 +0000

Step 1: Apply Global Styling

{
margin:0;
padding:0;
box-sizing:border-box;
}

Step 2: Style the Body

body{
background:#f3f4f6;
color:black;

Step 3: Design the Navigation Bar

Flexbox Layout
Sticky navigation
Background color
Hover effects

Step 4: Design the Hero Section

Profile image
Flex layout
Skill tags
Resume button

Step 5: Style the About Section

White card layout
Rounded corners
Shadow effects

Step 6: Style the Skills Section

CSS Grid Layout
Skill Cards
Hover Animation

Step 7: Style the Projects Section

Project cards
Hover effects
Box shadows

Step 8: Style Education Section

Two-column layout
Information cards
Clean typography

Step 9: Style Contact Section

Contact cards
Social media buttons
LinkedIn and Gitlab Links

Step 10: Create Responsive Design

@media(max-width:768px)

Portfolio Website HTML Page

Punitha — Sat, 18 Jul 2026 03:23:59 +0000

Step 1: Create the HTML Structure

<!DOCTYPE html>
<html>
<head>
</head>
<body>
</body>
</html>

Step 2: Add Meta Information

<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">

Step 3: Link CSS and Icons

<link rel="stylesheet" href="style.css">

Step 4: Create Navigation Bar

Menu Items

About 
Skills 
Projects 
Education 
Contact

Step 5: Create Hero Section

Hero Section

Profile Photo 
Name 
Job Title 
Technical Skills 
Resume Download Button

Step 6: Create About Me Section

Provides information about educational background and career interests.

Step 7: Create Technical Skills Section

SQL 
Power BI 
Excel
Python 
MySQL

Step 8: Create Projects Sections

Retail Sales Analysis Dashboard
Pharmacy Management System
Event Management System

Step 9: Create Education and Languages Section

Education details and language proficiency were displayed.

Step 10: Create Content Section

Email Address
Phone number
Location
LinkedIn Profile
Gitlab Profile

Step 11: Create Footer

A footer was added at the bottom of the page.

Data Analysis Expressions(DAX)

Punitha — Fri, 17 Jul 2026 02:04:40 +0000

What is DAX?

DAX(Data Analysis Expressions) is a formula language used in Power BI to create calculated columns, measures, and custom calculations.
DAX helps users perform advanced data analysis and create business metrics.

Why DAX is Used?

Perform calculations
Create KPIs
Calculate totals and average
Analyze trends
Create custom business metrics

How to Create a DAX Measure?

Step 1:
Modeling -> New Measure
Step 2:
Write the DAX formula
Step 3:
Press Enter
Step 4:
Use the measure in visuals

Common DAX Functions

SUM() - Calculates the total value

Total Sales = SUM(Sales[Sales Amount])

AVERAGE() - Calculates the average value

Average Salary = AVERAGE(Employee[Salary])

COUNT() - Counts the numbers of records

Total Orders = COUNT(Orders[Order ID])

MAX() - Returns the highest value

Highest Sales = MAX(Sales[Sales Amount])

MIN() - Returns the lowest value

Lowest Sales = MIN([Sales[Sales Amount])

Power Query Editor Workflow

Punitha — Thu, 16 Jul 2026 01:32:07 +0000

Step 1: Import the dataset

Open Power BI Desktop
Click Get Data
Select the Excel or CSV file
Click Transform Data to open Power Query Editor

Step 2: Explore the Power Query Editor Interface

Ribbon Panel
Queries Pane
Data Preview Area
Query Settings Pane
Formula Bar

Step 3: Check and Correct Data Types

Change incorrect types:

Text
Whole Number
Decimal Number
Data

Step 4: Clean the Data

Remove Duplicates
Handle Missing Values
Remove Unnecessary Columns

Step 5: Transform the Data

Rename Columns
Split Columns
Merge Columns
Format Text

Step 6: Create New Columns

Custom Column
Conditional Column

Step 7: Filter and Sort Data

Filter - Remove unwanted records
Sort - Arrange data in ascending or descending order

Step 8: Review Applied Steps

Check the Applied Steps pane
Verify each transformation

Step 9: Apply Changes

Click Close & Apply
Power BI loads the transformed dataset into the report view

Step 10: Build Reports and Dashboards

Create Cards
Charts
Maps
Tables
KPI visuals

Power Query Editor

Punitha — Wed, 15 Jul 2026 03:08:11 +0000

Data Preview Area(Center):
The Data Preview Area is located in the center of Power Query Editor. It displays the actual dataset in an tabular format(rows and columns).

Data Preview area helps:

View the data
Edit values
Check data quality
Apply transformations

Query Settings Pane(Right Side):
The Query Settings Pane is located on the right side of Power Query Editor. It display information about the selected query and all applied transformation steps.

Query Settings Pane helps:

Shows the query name

Formula Bar:
The Formula Bar displays the Power Query M language code generated for each transformation.
Formula Bar hepls:

View M code
Edit transformations manually
Create advanced data transformations

Column Headers:
Column Headers are located at the top of each column in the Data Preview Area.
Column Header helps:

Display column names
Show data types
Access filtering and sorting options

Status Bar:
The status Bar is located at the bottom of Power Query Editor.
Status Bar helps:

Number of rows
Number of columns
Query Loading status
Data profiling information

Power Query Editor

Punitha — Tue, 14 Jul 2026 02:58:12 +0000

Main Components of Power Query Editor

Ribbon Panel: Contains all commands used for data cleaning and transformation.
Queries Pane(Left Side): Displays all tables(queries) loaded into Power Query
Data Preview Area(Center): Shows the actual dataset in rows and columns.
Query Settings Pane(Right Side): Displays all transformations applied to the selected query.
Formula Bar: Shows the Power Query M code generated for each transformation.
Column Headers: Displays column names and data types.
Status Bar: Displays information about the dataset.

Main Tabs in Ribbon Panel

Home Tab - Used for basic data management operations.
Eg: Close & Apply, Refresh Preview, Remove Rows, Keep Rows, Replace Values, Merge Queries, and Append Queries
Transform Tab - Used to modify and transform data.
Eg: Change Data Type, Split Column, Merge Columns, Pivot Column, Unpivot Column, and Format Text
Add Column Tab - Used to create new columns.
Eg: Custom Column, Conditional Column, Index Column, Date Column, and Duplicate Column
View Tab - Used to control what is displayed in Power Query Editor.
Eg: Formula Bar, Query Settings, Column Quality, Column Distribution, and Column Profile

Query Pane(Left Side):
The Queries Pane is located on the left side of the Power Query Editor. It display all the tables(queries)that have been loaded into Power BI.

Query Pane helps:

View all loaded tables
Switch between different queries
Manage multiple datasets
Rename queries for better understanding
Works: Select Query, Renaming Query, and Delete Query

KPI Card and Power Query Editor

Punitha — Mon, 13 Jul 2026 02:02:41 +0000

Step 1: Load the Dataset

Open Power BI Desktop
Click Get Data
Import the dataset
Click Load

Step 2: KPI Card

Select KPI Card
Drag Order ID -> Value -> Count
Drag Date -> Trend Axis -> Day
Drag Order ID -> Target -> Count
Rename title Order Day Count

Power Query Editor

Power Query Editor is a data transformation and data cleaning tool in Power BI. It is used to clean, modify, filter, and prepare data before creating reports and dashboards.

Main Components of Power Query Editor

Ribbon Panel
Queries Pane(Left Side)
Data Preview Area(Center)
Query Settings Pane(Right Side)
Formula Bar
Column Headers
Status Bar

Multi Cards, Gauge and Table

Punitha — Sat, 11 Jul 2026 11:31:35 +0000

Step 1: Import Data

Open Power BI Desktop
Click Get Data
Select your Excel/CSV file
Click Load

Step 2: Card Visual

Select Card Visual
Drag Job Title -> Value
Drag Salary Year -> Value -> Average
Drag Salary Hour -> Value -> Average
Rename the titles

Step 3: Gauge Chart

Select Gauge Chart
Drag Salary Year -> Value -> Sum
Drag Salary Year -> Minimum Value -> Min
Drag Salary Year -> Maximum Value -> Max
Drag Salary Year -> Target Value -> Median
Rename the title

Step 4: Table Chart

Select Table Chart
Drag Job Title Short -> Columns
Drag Salary Year -> Columns -> Average
Drag Salary Hour -> Columns -> Average
Go to format visual -> Cell elements -> On the Data Bars

Map, Ribbon and Table Charts

Punitha — Fri, 10 Jul 2026 08:51:50 +0000

Step 1: Import the dataset

Open Power BI Desktop
Click Get Data -> Excel/CSV
Select your dataset
Click Load

Step 2: Map Chart

Select Map Chart
Drag Country -> Location
Drag year -> Bubble Size -> Sum
Rename Sum of 2025 by Country

Step 3: Ribbon Chart

Select Ribbon Chart
Drag Date -> X-Axis
Drag Silver Change -> Y-Axis -> Sum
Drag Gold Change -> Y-Axis -> Sum
Rename Gold and Silver Plot

Step 4: Table Chart

Select Table Chart
Drag Country -> Columns
Drag 2025 -> Columns -> Sum
Drag 2024 -> columns -> Sum
Rename Country-wise Comparison

Area - Line Chats

Punitha — Thu, 09 Jul 2026 05:42:35 +0000

Step 1: Import Data

Open Power BI Desktop
Click Get Data -> Excel/CSV
Select your dataset
Click Load

Step 2: Line Chart

Select Line Chart
Drag Order Date -> X-Axis
Drag Order ID -> Y-Axis -> Count
Rename title as Order Count

Step 3: Stacked Area Chart

Select Stacked Area Chart
Drag Order Date -> X-Axis
Drag Sell -> Y-Axis -> Sum
Drag Store Name -> Legend
Rename title as Order value by Store

Step 4: Line Chart

Select Line Chart
Drag Order Date -> X-Axis
Drag Order ID -> Y-Axis -> Count
Go to the further analyses visual -> Turn ON Trend Line
Rename title as Order Count

Step 5: 100% Stacked Ares Chart

Select 100% Stacked Area Chart
Drag Order Date -> X-Axis
Drag Sell -> Y-Axis -> Average
Drag Store Name -> Legend
Rename title as Order Value by Store