Prashanth Yadamala's CV

EDUCATION

Master of Engineering Science (Manufacturing Engineering and Management)
Sep 2019 – Sep 2021
UNSW Sydney | WAM: 83.5

Bachelor of Engineering (Mechanical Engineering)
Jul 2014 – May 2018
Manipal Institute of Technology | CGPA of 8.62

PROJECTS

Analysis of LinkedIn Data Analysis Job Postings in Australia - Personal Project

(Jun 2024 – Jul 2024)

• Analysed 400+ LinkedIn data analyst job postings in Australia using Power BI visualizations to provide insights into the current job market.
• Collected data from the LinkedIn website’s job section using Python library requests and pandas to scrape and store respectively.
• Cleaned and transformed the collected data in Power Query to maintain data integrity and support the analysis needs.
• Aggregated and visualized the data using DAX measures and charts in the form of a professional Power BI report.

Customer Retention Rate using Cohort Analysis in Power BI - Personal Project

(May 2024 – Jun 2024)

• Built as a Power BI report leveraging transactional data from Adventure Works by using cohort analysis to analyse the customer retention rate.
• Constructed a matrix visualization using DAX measures to analyse the retention rate of newly acquired customers in the preceding 12 months.
• Visualized the monthly breakdown of new vs returning customers over time.

Market Basket Analysis in Power BI (Retail Sales Data) - Personal Project

(Apr 2024 – May 2024)

• Designed a comprehensive Market Basket Analysis Power BI report and dashboard leveraging transactional data from the Adventure Works retail sales dataset.
• Employed SQL (SQL Server) and Power BI for data cleaning, transformation, analysis, and visualization.
• Analyzed customer purchase patterns to uncover significant correlations to identify the top 10 products bought most frequently based on season.
• Built a table visualization using DAX measures to identify the products bought most frequently with a selected product to optimize product placement and offer promotional product bundles.

Hotel Data Reporting and Analysis using Power BI Dashboards - Personal Project

(Mar 2023 – Apr 2024)

• Created a Power BI report to give insights using visualizations into sales data, hotel bookings, customer data and trends over time.
• Performed data cleaning and transformation in SQL Server to maintain data integrity.
• Compiled the data into a star schema data model in Power BI using the hotel transactional data as the fact table.
• Analysed the sales trends over time and customer data to discover growth opportunities.

Exploratory Data Analysis and Customer Segmentation Analysis - Bellabeat Case Study

(Dec 2023 – Jan 2024)

• Performed an exploratory analysis and a customer segmentation using over 1400 days of Fitbit data.
• Transformed, merged and cleaned data using Excel and SQL to ensure data integrity using the ROCCC system.
• Visualised the data using R Studio using ggplot, dplyr and tidyverse libraries to perform an exploratory analysis of the data.
• Segmented the customers-based average daily steps and average daily device usage to explore opportunities to improve market share.
  
  

WORK EXPERIENCE

Student Project Consultant – PVCESE Education Technology Support

(Jun 2021 – Aug 2021) University of New South Wales (UNSW Sydney)

• Formatted, analysed and visualized the data in Microsoft Excel using data collected from over 100 student responses through surveys and interviews to gain insights into experience with ET support.
• Presented the PVCESE team at UNSW with data-driven recommendations to improve awareness and visibility of ET support options for students at UNSW.
• Deployed changes (based on recommendations) showed an 85% month-on-month increase in interactions with ET support resources.
  
  
  

CERTIFICATIONS

• Microsoft Certified: Power BI Data Analyst Associate (PL-300).
• Google Data Analytics Professional Certificate, Coursera.
• Microsoft Power BI Data Analyst Specialization, Coursera.
  
  

SKILLS

• SQL (SQL Server, MySQL, BigQuery)
• Power BI (Power Query, DAX)
• Excel (VLOOKUP, Pivot Tables, Conditional Formatting)
• Python (Pandas, NumPy, MatPlotLib)
• R (Ggplot, Dplyr, Lubridate, Tidyr)
• Tableau Public
• Minitab