Payal

PROJECTS Czechoslovakia Banking Financial Data Analysis

•Successfully performed data cleaning tasks and created an AWS account, demonstrating proficiency in basic data preparation and cloud platform management. 04/2023 – 05/2023

•Created and managed buckets in AWS S3, assigned roles, and implemented policies to ensure secure data storage and access.

•Established a Snowflake environment by creating warehouses, databases, schemas, and tables, showcasing advanced data cleaning skills and data organization capabilities.

•Implemented storage integration, file format, and stage creation in Snowflake, ensuring efficient data processing and storage. •Developed end-to-end data pipelines, including notification alerts, stored procedures, and tasks, automating data management processes and enhancing efficiency. Built a strong connection between Snowflake and Power BI, enabling data extraction, transformation, and dashboard creation for insightful data visualization. Retail Data Analysis

•Implemented a Retail Data Analysis Dashboard using Snowflake, AWS, Python, Power BI, and Power BI Query. 03/2023 – 04/2023

•Established a seamless data upload and tracking system by connecting AWS S3 and Snowflake.

•Conducted comprehensive Exploratory Data Analysis (EDA) using Python and Snowflake connectors, ensuring data cleanliness.

•Automated the EDA process through Jupyter Lab and implemented scheduled refresh using jupyter_scheduler and jupyterlab-scheduler.

•Created interactive visualizations and reports in Power BI, utilizing DAX for calculated measures and columns.

•Showcased valuable insights on customer behavior patterns, campaign effectiveness, and competitive analysis for informed decision-making and improved business intelligence. Demonstrated proficiency in AWS, Snowflake, Python, Power BI, and Power BI Query, along with strong data analysis, visualization, and automation skills. Deloitte Case Study

•Analyzed a time series data of 200 countries from the World Bank, focusing on CPI, exchange rate, and exports for the period 1990-2018. 02/2023 – 03/2023 •Prepared the data for visualization in Excel, ensuring data quality by removing null values and duplicates.

•Utilized Power Query Editor in Power BI to further refine and transform the data, ensuring its readiness for analysis.

•Composed complex queries in Snowflake to perform calculations and created tables, which were then loaded into Power BI for analysis.

•Implemented DAX queries to create measures and calculated columns, providing insights and facilitating the extraction of relevant data.

•Created informative visualizations in Power BI, enabling the identification of patterns and trends related to CPI, exchange rates, and export merchandise.