Portfolio - Kiran V | Codebasics

Hello, I am

Kiran V

Data Aspirant

Resume

2

PowerBI
Projects

1

SQL
Project

About

I am Kiran.V from Bengaluru, a Data Enthusiast, who has
various certifications in Data Analytics from Accenture-
Forage, Great Learning(SQL), CodeBasics,etc. I have
completed various industry level projects in Power BI,
SQL,Python-Pandas,etc. I hope that I will be the suitable
candidate to seek employment opportunities in the
booming Data industry.

Key

Skills

pandas

matplotlib

sql

python

My

Projects

Analysis of the 'Air Particulate Matter Of Delhi' Dataset.

Dataset of Air Particulate Matter of Delhi was obtained from Kaggle and analyzed using Power BI.
DAX measures were created in order to calculate various parameters and finally various charts were created to visualize the data.

Analysis of the 'Netflix-Movies and TV Shows' Dataset.

Netflix-Movies and TV Shows Dataset was obtained from Kaggle.
Analyzed by using various DAX measure and Charts.
English TV shows were the highest streamed category among all the categories.

SQL Queries For Business Requirements Of Atliq Mart Using SQL Database

Data obtained from Atliq Mart(CodeBasics). Queries were written in order to understand which promotion did well and which did not( which were introduced during Diwali sales).

Awards

& Certificate

SQL for Data Science

Data Analytics and Visualisation Job Simulation

Assessment certificate for SQL(Basic)

Contact Me

Email

[email protected]

Github

https://github.com/KiranV98

https://www.linkedin.com/in/kiran-v-15408a2a3/

Call

+91 8050308935

Kiran V

Data Aspirant

Download Resume

Resume

PowerBI Project

Analysis of the 'Air Particulate Matter Of Delhi' Dataset.

Dataset of Air Particulate Matter of Delhi was obtained from Kaggle and analyzed using Power BI. DAX measures were created in order to calculate various parameters and finally various charts were created to visualize the data.

View Project
on GitHUB

Dashboard for the Dataset 'Air Particulate Matter of Delhi'. DAX measures were created for Median, Max, Average of four Quarters,etc

Cleaned Data. Data was cleaned using Power Query

Project Details

ETL of Dataset for Particulate matter(PM2.5 and PM10,Duration: 24hrs) from Delhi Air was carried out • Using Power Query.
DAX measures like median of PM2.5, Average of PM2.5, Max-value of PM2.5 and average values of PM2.5 divided into four quarters (Out
of 24Hrs) was calculated(186.64, 185.74, 95.84, 194.42 )
The insights drawn using Card, Multi-card, Line Chart, etc. indicate that 4th Quarter(6PM to 12AM) has the highest average of PM2.5 i,e.
194.42.
Results show that reducing the particulate matter during the 4th quarter hours(6PM to 12AM) could potentially reduce the pollution.
• Tech Stack: Power BI, DAX.

Live Interactive Dashboard

PowerBI Project

Analysis of the 'Netflix-Movies and TV Shows' Dataset.

Netflix-Movies and TV Shows Dataset was obtained from Kaggle. Analyzed by using various DAX measure and Charts. English TV shows were the highest streamed category among all the categories.

View Project
on GitHUB

Dashboard for the data 'Netflix-Movies and TV Shows'

Cleaned data along with new measures and columns.

Project Details

Data obtained from Kaggle was cleaned using Powe Query.
Measures were created using DAX for percentage of total watch hours of English over Non-English languages.(175.25% greater than
non-English)
Clustered column chart for comparing TV Shows and movies watch hours was created with language as legend(English TV shows shows
highest watch hours, 43bn).
Stacked bar chart for sum of weekly watch hours by show title and language(Stranger things(English) shows highest watch hours i,e.
2.7bn).
Results point out that increasing the number of English TV shows could potentially increase the number of subscribers.
• Tech Stack: Power BI, DAX, Power Query.

Live Interactive Dashboard

SQL Project

SQL Queries For Business Requirements Of Atliq Mart Using SQL Database

Data obtained from Atliq Mart(CodeBasics). Queries were written in order to understand which promotion did well and which did not( which were introduced during Diwali sales).

View Project
on GitHUB

Queries from 1 to 3

Queries from 4 to 5

Project Details

Listing of products with price greater than Rs.500 and with the promo type of 'BuyOneGetOne'using JOIN and WHERE clauses
Generating the COUNT of stores in each city using GROUP BY clause.
Calculating and ranking Incremental Sold Quantity (ISU%) using CTE,JOIN, DENSE RANK,etc clauses.
Generating Increment Revenue (IR%) across the categories using JOIN,CTE, DENSE RANK, etc clauses.
• Tech Stack:SQL

Hello, I am

Kiran V

2

1

About

Key

My

Analysis of the 'Air Particulate Matter Of Delhi' Dataset.

Analysis of the 'Netflix-Movies and TV Shows' Dataset.

SQL Queries For Business Requirements Of Atliq Mart Using SQL Database

Awards

Contact Me

Email

Github

Linkedin

Call

Kiran V

Download Resume