SHRIRAM M

Hey there, welcome to my portfolio! This is Shriram M, I'm all about diving into data and turning it into something super useful. You know, like those cool insights that help businesses make big decisions? Yeah, that's my jam.

So, here's the deal: I started out studying Civil engineering, but then I got hooked on the whole data scene. I mean, who wouldn't find it exciting to help businesses make smart moves based on what the numbers are telling us? It's like being a detective, but with spreadsheets instead of magnifying glasses!

Check my portfolio below – they're like my data babies, each one showing off what I can do with Power BI and Tableau.

I'm all about curiosity and learning new things, so I'm excited to jump into the data game with your team. Let's team up and make some serious data magic happen!

Walmart Super store sales analysis using Power BI.

• To identify top products that contribute to the revenue.
• Analyze customer purchase behavior to estimate what items are more likely to be purchased individually or in combination with some other products.
• Visualizing sales and profit using various parameters.
  Creating a detailed report.

 Cyclist bike share analysis using Tableau.

• This report presents an analysis of Cyclist bike share data using Tableau to gain insights into the usage patterns of casual riders and annual members.
• As a junior data analyst at Cyclist, the objective is to maximize the number of annual memberships to increase company profitability.
• By understanding how casual riders and annual members utilize Cyclist bikes differently, the marketing team aims to develop a data-driven marketing strategy to convert casual riders into loyal annual members.

 Spotify trend Analysis using Tableau.

• Create a basic dashboard to understand top tracks and artists by country.
• Understanding the different patterns of music listeners across the globe.

Adidas Sales dataset analysis using SQL

• This project aims to analyze Adidas sales data using SQL to uncover valuable business insights. By examining sales performance, regional trends, and customer behavior, the analysis will help optimize inventory, pricing, and marketing strategies.
• SQL Analysis & Queries:
  Sales performance analysis.
  Product and category-based revenue analysis.
  Regional sales breakdown.
  Profitability evaluation.
  Customer segmentation based on purchase history.

Spotify datset analysis using Tableau

• The goal of this project is to analyze Spotify’s dataset to gain insights into user listening behavior, track popularity trends, and evaluate business performance.
• User Behavior Analysis: Identify peak listening hours, favorite genres, and regional trends.
• Song Popularity Trends: Determine factors influencing a song’s success (tempo, energy, danceability).
• Artist Performance: Analyze top-performing artists and how their streams vary over time.