Pramod Raghuwanshi

Data Validation Tool:

• Engineered a Python CLI tool to automate cross-platform data validation, leveraging PySpark for scalability, and boosting migration efficiency by 90%, thereby reducing errors in data migration.
• Streamlined the validation process, reducing manual effort by approximately 80% and time by 90%, increasing operational efficiency and allowing team members to focus on more strategic tasks.
• Ensured comprehensive data validation, covering data types, schema consistency, aggregation checks, numeric columns, and row-level validation. This amplify the reliability of data used in business operations.

Teradata to Snowflake Migration:

• Successfully migrated data from Teradata to Snowflake, leveraging PySpark for efficient data processing, enhancing capabilities, and reducing maintenance costs.
• Validated stored procedure functionality during the transition, ensuring seamless operations and minimizing migration downtime.
• Ensured consistency between original Teradata data and migrated Snowflake data, preserving data integrity for informed decision-making.
• Verified data integrity and accuracy post-migration, using PySpark, providing stakeholders assurance of successful migration and reliable Snowflake data for operations.
• Collaborated closely with the reporting team to improve data accuracy in reports and enhance the quality of insights derived from the data.

Distribution Business Unit:

• Managed transactional and operational data related to sales and expenses, providing a reliable source of data for business decision-making and contributing to the overall efficiency of the business operations
• Built BTEQ scripts to load data from raw tables to target tables, applying necessary transformations, improving the data quality and ensuring that the data is in the right format and structure for further analysis
• Created views on top of target tables for the reporting team, enabling faster and more efficient data retrieval, which led to reduction in time spent on generating reports
• Collaborated closely with business users to understand requirements and ensure effective data transformation, resulting in a increase in user satisfaction with the data.

Power System Business Unit:

• Worked with engine and parts data and transformed it to get the useful insights for business users, enabling them to make data-driven decisions that Enhanced operational efficiency
• Constructed stored procedures to automate repetitive tasks, reducing the time spent on these tasks and allowing the team to focus on more strategic initiatives
• Created comprehensive PowerBI reports that offered valuable insights into the business, leading to a 50% improvement in business performance metrics
• Optimized queries to improve performance, especially for critical reports, resulting in a 10 to 15% reduction in report generation time and a more efficient data analysis process
• Developed SSIS packages for data integration and workflow applications, improving the data processing speed and ensuring data is readily available for business use.