Siddhesh Parab

Detail-oriented Data Analyst skilled in SQL, Power BI, Python, and Excel for data visualization, modelling, and analysis. Experienced in writing complex queries, optimizing database performance, and managing ETL processes. Proficient in data wrangling, DAX queries, ETL processes and advanced analytics to transform raw data into actionable insights. Passionate about solving business problems through data-driven decision-making.

• Simplilearn, IBM
• PwC Switzerland – Power BI Job Simulation – March 2025

Power BI Project - Best Restaurant Analysis

• Designed an interactive Power BI dashboard to evaluate restaurant performance across different cities.
• Conducted data transformation and cleansing, improving data accuracy by 30 %.
• Created DAX measures for key metrics like average rating, cost per meal and cuisine diversity.

Power BI Project - Netflix Data Analysis Dashboard

• Designed an interactive Power BI dashboard to analyze Netflix's movie and TV show dataset
• Processed and visualized 8,803 titles, categorized by genre, rating, release year and country.
• Built dynamic filters and KPIs to compare content distribution across different regions.
• Created insightful visualizations on top genres, most popular ratings and year-wise content trends.
• Enhanced data storytelling with DAX measures and calculated columns for key insights.

Python Project - Airline Data Analysis

• Analyzed an airline dataset using Python for data preprocessing and exploration.
• Used Pandas to clean, structure, and extract key statistics from the data.
• Identified missing values and performed data wrangling for better insights.
• Created visualizations, including pie charts, histogram to analyze demographic distributions.
• Derived actionable insights to support data-driven decision-making in the airline industry.

SQL Project - Music Database Analysis

• Identified the senior-most employee based on job title.
• Analyzed invoice data to determine the countries with the highest sales.
• Retrieved the top three highest invoice values.
• Identified the city generating the highest revenue to plan a promotional music festival.
• Determined the best customer based on total spending.
• Extracted and listed Rock music listeners, ordering results alphabetically by email.
• Identified the top 10 artists with the most Rock tracks.
• Retrieved all tracks with a length longer than the average song duration.

• Date Of Birth: 07/08/2001
  Marital Status: Single
  Gender: Male
  Hobbies: Listening Music, Cricket, Chess