Ayanava Debnath

• Proficient in data analysis techniques, data cleaning, and data visualization.
• Proficient in Python for data analysis.
• Skilled in creating interactive dashboards and reports using Power BI.
• Strong knowledge of SQL for querying and managing relational databases.
• Advanced proficiency in Excel for data analysis and reporting.
• Effective at identifying and solving complex data-related problems.

Highly motivated Mainframe DBA Support professional with 2 years of experience in SQL and a strong foundation in Python, Power BI, SQL, and Excel.Seeking a transition into a Data Analysis role to leverage data-driven insights for informed decision-making.

Completed online courses in Data Analysis using Python and Power BI.

Participated in data analysis projects, demonstrating the ability to apply data analysis techniques to real-world scenarios.

SQL (Basic) HackerRank

1. Conducted comprehensive analysis of Israel-Palestine conflict fatalities dataset (Oct 2020 - Oct 2023) using Python. Key findings include fluctuating fatality rates, stable periods from 2010 to 2013, a focus on fatalities among ages 19-25 with a gender disparity, and a concentration of incidents in the Gaza Strip, particularly in Gaza, North Gaza, Khan Yunis, and Rafah. The study revealed significant Palestinian losses, non-combatant involvement, and common causes of injury such as gunfire, explosions, and shelling. Israeli security forces were primarily responsible, with input from Palestinian and Israeli civilians. Data quality was ensured through value replacement, duplicate removal, and column exclusion.

2.Conducted a comprehensive analysis of IMDb data spanning 2006 to 2016 using Python, providing unique insights into the entertainment industry. The study highlighted the prominence of directors like Christopher Nolan and the financial success of James Cameron. It dispelled the myth that fame guarantees movie revenue and unveiled nuances in the film world. The year 2016 emerged as a standout with increased production and record-high revenue. The analysis also showed the ideal movie runtime, the correlation between ratings and revenue, and identified standout films like 'The Dark Knight' and 'Star Wars: Episode VII - The Force Awakens.' Notably, data quality was maintained by addressing missing revenue and metascore entries.

3.Developed an insightful Power BI dashboard for the Data Professional Survey dataset, offering an intuitive interface for deep data exploration. Users can effortlessly analyze survey demographics, roles, industries, and tool usage, uncovering key insights. Notable findings include high salaries for data scientists, successful career transitions, gender pay parity, Python's dominance, balanced challenges, salary dissatisfaction, and positive work-life balance sentiment (5.74/10).

4.Led a data-driven exploration of app development by using SQL, providing valuable insights to an aspiring app developer. Conducted comprehensive Exploratory Data Analysis (EDA), revealing trends such as the advantage of paid apps and the impact of language support. Highlighted genre-specific challenges and emphasized the importance of detailed app descriptions and high average ratings for new apps. Equipped the stakeholder with strategic guidance to navigate the dynamic app development landscape, combining data exploration and analysis.