Anthaiah Gangarapu
Data Engineer
Hyderabad
Summary
Results-driven Data Analyst with internship experience at Revature, skilled in Python, BigQuery, predictive modeling, trend analysis, and data visualization. Experienced in developing data-driven solutions to improve inventory management and forecasting accuracy. Proven ability to analyze complex datasets and deliver actionable insights that support strategic decision-making. Strong team collaborator focused on performance improvement and business impact.
Overview
3
3
Certifications
Work History
Data Analytics
Revature
Hyderabad
04.2025 - 06.2025
- Applied advanced data analytics techniques to identify patterns and trends in system performance, leading to targeted performance improvements.
- Developed predictive models to enhance inventory management strategies, improving forecasting accuracy and reducing stock-related inefficiencies.
- Conducted trend analysis using analytics tools to support strategic decision-making across operations and finance departments.
- Contributed to end-to-end data workflows, including ingestion, transformation, and analysis using Python, SQL, Hadoop, Hive, PySpark, and BigQuery.
- Analyzed YouTube and Spotify datasets to uncover music trends, user behavior, and content performance insights.
- Leveraged data analytics tools to gain insights into system usage patterns, identifying opportunities for resource optimization and cost reduction.
Education
Master of Computer Applications [MCA] - CSE
KL University
Vijayawada 04.2001 -
Bachelor of Science - Computer Science
Vignan Degree & PG College
Guntur 04.2001 -
Skills
Projects
YouTube Data Analysis using Python & MySQL
- Cleaned and analyzed the YouTube 2025 dataset to uncover trends in video length, content type, engagement, and subscriber growth.
- Migrated data into MySQL and used complex queries to extract business insights.
- Visualized key metrics using Python libraries for stakeholder reporting.
Tools: Python, MySQL, Pandas, Matplotlib, Git
Spotify Songs Data Analysis – Phase 1
- Processed large-scale Spotify data to analyze genre popularity and audio features like tempo and energy.
- Applied PySpark and Hive on Hadoop for scalable data transformation and used BigQuery for querying.
- Delivered visual reports to guide strategy for music platforms and artists.
Tools: Python, MySQL, Pandas, Matplotlib, Git
Serverless Orchestrated ETL Pipeline – Phase 2 (Advanced)
- Built a fully automated ETL pipeline on GCP to ingest, transform, and load Spotify data into BigQuery.
- Used Cloud Composer (Airflow) to orchestrate workflows triggered by file uploads to GCS.
- Implemented Apache Beam (Dataflow) jobs for transformation and real-time data integration.
- Improved pipeline scalability, automation, and data freshness.
Tools: GCP (GCS, Cloud Composer, Pub/Sub, Dataflow), BigQuery, Python
Certification
Cisco Network Academy
Timeline
Data Analytics
Revature
04.2025 - 06.2025
Master of Computer Applications [MCA] - CSE
KL University
04.2001 -
Bachelor of Science - Computer Science
Vignan Degree & PG College
04.2001 -
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