Ganesh Bogineni

GANESH BOGINENI OH, USA •-• +1 - • LinkedIn SUMMARY Data Analyst with over 3+ years of experience in data visualization, statistical analysis, and machine learning techniques to extract actionable insights. creating dashboards using Tableau and Power BI, developing scalable ETL pipelines with AWS and Azure services, and executing large-scale data processing using Apache Spark and Hadoop. Skilled in crafting SQL queries, Python-based data analysis, and statistical modeling to support business and optimize operational workflows. collaborating cross-functionally to solve complex problems. EDUCATION Master of Science in Computer Science Wright State University, Fairborn, Ohio Aug 2021 – Apr 2023 Bachelor of Computer Science Gitam University, Visakhapatnam, Andhra Pradesh Aug 2016 – Apr 2020 SKILLS ● ● ● ● ● ● ● ● ● ● ● Data Visualization Tools: Tableau, Power BI, Plotly Dash Databases: MySQL, MS SQL Server, Azure SQL Database, AWS RDS, MongoDB Programming Languages: Python (Pandas, NumPy, Matplotlib, Seaborn), R, SQL, VBA Cloud Platforms: AWS (S3, RDS, Redshift, Glue), Azure (Data Factory, Data Lake, Synapse Analytics) Big Data Tools: Hadoop HDFS, Apache Spark, Hive, SparkSQL ETL Tools: AWS Glue, Azure Data Factory, SSIS Statistical Analysis: Hypothesis Testing, Regression Analysis, T-tests, ANOVA, MANOVA Machine Learning: Feature Engineering, Decision Trees, Logistic Regression, Random Forest Version Control & CI/CD: Azure DevOps, Git Tools & Applications: Jupyter Notebook, MS Excel (Pivot Tables, VBA), MS PowerPoint Data Analysis Techniques: A/B Testing, Segmentation, Cohort Analysis, EDA PROFESSIONAL EXPERIENCE Allstate OH, USA Data Analyst Jun 2023 – Present ● Developed Power BI dashboards to provide real-time insights into business metrics, integrating multiple data sources such as Azure SQL Database and Azure Data Lake, with a strong focus on Data Wrangling to clean and prepare raw data for analysis. ● Implemented robust data pipelines using Azure Data Factory to extract, transform, and load data from diverse sources, including JSON, CSV, and APIs. ● Designed relational schemas in SQL Server to enable efficient querying and visualization for Power BI reports. ● Automated deployment of Power BI datasets and reports using Azure DevOps pipelines, ensuring version control and CI/CD integration. ● Conducted Exploratory Data Analysis (EDA) with Python (using Matplotlib and Seaborn) to uncover actionable trends in customer purchase patterns. ● Conducted statistical modeling, including T-tests, ANOVA, and predictive analysis, to measure campaign performance and optimize marketing strategies. ● Preprocessed data for machine learning workflows, handling tasks like feature engineering, data normalization, and missing value imputation using Python. ● Leveraged Azure Synapse Analytics to process and analyze large datasets, optimizing queries with Spark Pools for high-performance computing. Brightmind Technogies India Data Analyst Aug 2019 – Jul 2021 ● Designed and maintained dynamic Tableau dashboards to monitor and visualize real-time KPIs, integrating A/B testing frameworks with external APIs and internal databases, while ensuring adherence to data governance standards. ● Conducted in-depth data mining and data cleaning to analyze customer purchase behavior, leveraging AWS services (S3, RDS) for scalable data storage and management. ● Built ETL pipelines to extract data from various sources, utilizing AWS Glue for data transformation, automated workflows, and ensuring compliance with data governance policies. ● Engineered MySQL table schemas and implemented optimized stored procedures for efficient customer data processing. ● Queried and validated large datasets using Python with Pandas and NumPy to ensure data integrity, detect inconsistencies, and perform data cleaning. ● Developed and evaluated machine learning models (e.g., Decision Trees, Random Forest) to predict customer retention, using data stored in AWS Redshift. ● Performed statistical analysis, including hypothesis testing and regression modeling, with R to derive actionable insights that increased sales conversion rates. ● Automated data ingestion workflows into AWS S3 using Python scripts and integrated data with Hadoop HDFS for distributed processing. ● Leveraged Apache Spark for analyzing datasets exceeding 2TB, utilizing SparkSQL for advanced querying and aggregations. ● Communicated insights to stakeholders using Tableau dashboards, Jupyter Notebook, and detailed presentations in MS PowerPoint. CERTIFICATIONS ● ● ● Microsoft Certified: Azure Administrator Associate Microsoft Certified: Data Analyst Associate AWS Certified Data Analytics Specialty