Data Analyst Power Bi
Resume:
Madhuharika Lingampally
Email: *************@*****.***
LinkedIn: https://www.linkedin.com/in/madhuharika/
Professional Summary:
Data Analyst with 10+ years of expertise in Power BI, Tableau, Snowflake, SQL, Azure, Excel, and Python, Proven track record in Data Analysis, ETL, Data Warehousing, and Data Modeling, creating interactive PowerPoint reports, monitoring platform health, and ensuring optimal performance of Power BI. Adept at leading cross-functional teams, mentoring junior analysts, and driving data-driven decisions for business requirement.
Adept at transforming raw data into actionable insights that drive strategic decisions and business growth. Proven expertise in data cleaning, data transformation, statistical analysis, and reporting. Skilled in developing and automating reporting systems, creating interactive dashboards, and performing complex data analysis to identify trends, outliers, and opportunities for optimization. Highly proficient in SQL, Power BI, Python, Snowflake and Excel, with a deep understanding of ETL processes, data modeling, and data governance. A collaborative team player, skilled at working with stakeholders to align technical solutions with business goals and enhance operational efficiency.
Data cleaning and data transformation using Python, SQL, and Excel.
Proficient in Power BI, Excel, and Tableau to create detailed, user-friendly reports and dashboards that provide insights into business performance.
Strong background in statistical analysis, applying methods like regression analysis, hypothesis testing, and trend analysis to draw meaningful conclusions from large datasets.
Experienced in writing and optimizing complex SQL queries for data extraction, transformation, and reporting from relational databases (SQL Server, Oracle).
Expertise in designing and implementing ETL processes to ensure accurate and timely data integration across various systems and platforms.
Experienced in creating and configuring data pipelines in Azure Data Factory to efficiently move, transform, and load (ETL) data from source systems to target destinations, ensuring data accuracy and consistency.
Experienced in optimizing data storage and processing costs in Azure by implementing efficient data storage formats, partitioning strategies, and performance tuning techniques within Azure Blob Storage, Azure Data Factory, and Azure Databricks.
Knowledgeable in data modeling (Star Schema, Snowflake Schema) and creating KPIs to track performance metrics for decision-making.
Proficient in Python for data analysis (Pandas, NumPy, Matplotlib) and R for basic statistical analysis. Adept in ensuring data accuracy, consistency, and compliance with internal standards for high-quality reporting and analysis.
Technical Skills
Tools: Power BI, Tableau, Snowflake, SQL Server, Azure Data Factory, SSIS, SSAS,PowerPoint Reporting, Excel
Languages: SQL, Python (Pandas, NumPy), DAX
Data Modelling: Star Schema, Snowflake Schema, Relational and Dimensional Modeling.
Other: Agile/Scrum, JIRA, Git, Data Governance, Analytical Ability
Certifications
Microsoft Certified: Power BI Data Analyst
Microsoft Certified: Azure Fundamentals
Oracle Certified Associate (OCA)
Professional Experience:
State of Ohio Jan 2025 – Present
Senior Data Analyst
Responsibilities:
Designed and developed advanced Power BI dashboards to analyze customer behaviours, transactional data, and financial metrics.
Aggregate and transform raw data into actionable formats for reporting and predictive analysis.
Conducted trend analysis, forecasting, and predictive modeling using Python (Pandas, NumPy) to uncover new business opportunities and optimize marketing campaigns.
Collaborated closely with business stakeholders and department heads to define business requirements and transform them into technical solutions, ensuring alignment with organizational objectives.
Ensured data quality and consistency through routine data audits, validation checks, and the implementation of best practices in data governance.
Utilized advanced statistical methods (regression analysis, hypothesis testing) to analyze customer satisfaction data and improve client retention strategies.
Mentored junior analysts and provided training on Power BI, Snowflake, and Python scripting.
Environment: Power BI, Snowflake, SQL Server, Python (Pandas, NumPy), SSIS, JIRA, Git, Excel.
United Airlines Jan 2022 – Dec 2024
Data Analyst
Delivered actionable insights from airline performance data, contributing to a 15% improvement in operational efficiency.
Automated data reporting processes using SQL and Python, reducing report generation time by 40%. Built interactive Power BI dashboards to track KPIs for customer behaviour, financial performance, and flight operations. Streamlined data workflows and enhanced reporting accuracy, leading to improved decision-making for senior management.
Analyzed large datasets (from SQL Server, SharePoint, Cloud sources) to uncover actionable insights for business performance optimization.
Implemented data ingestion pipelines using Azure Blob storage and Azure Data Factory (ADF), facilitating the seamless extraction, transformation, and loading (ETL) of large volumes of structured and unstructured data into analytics platforms.
Conducted data analysis and reporting using SQL and Power BI, providing actionable insights to improve business processes and strategy.
Designed Snowflake-based data models to optimize large-scale data processing and reporting, increasing the speed of data queries.
Ensured data integrity and accuracy by performing data validation, quality checks, and troubleshooting any discrepancies in reports.
Integrated Azure Databricks with Power BI for advanced analytics and visualization, enabling stakeholders to interactively explore and visualize insights derived from big data analytics.
Created and maintained recurring reports, including weekly/monthly performance dashboards for different business units. Developed automated data pipelines to ensure data accuracy and timeliness, integrating diverse data sources into one cohesive reporting structure.
Conducted ad-hoc data analysis on customer behaviour and operational metrics, providing stakeholders with real-time insights.
Ensured data integrity and cleanliness by performing data quality checks and applying best practices for data governance.
Environment: SQL Server, Power BI, Snowflake, Microsoft Azure, Excel, Python, JIRA, Git.
Duke Energy Nov 2017 – Jan 2022
Data Analyst
Automated routine reporting processes, improving efficiency and reducing manual labor by 30%.
Performed data analysis initiatives that helped identify cost-saving opportunities, resulting in a 20% reduction in energy distribution costs. Created comprehensive, interactive Power BI dashboards to monitor key performance metrics across energy operations.
Designed, developed, and deployed Power BI dashboards for visualizing operational data, ensuring stakeholders had easy access to critical performance indicators.
Conducted in-depth statistical analysis on energy performance data, identifying trends, anomalies, and actionable insights.
Analyzed complex datasets using Power BI and SQL to create automated reports for senior management.
Extracted and transformed data from multiple sources, including SQL Server and flat files, into Power BI for visualization and reporting.
Transformed raw data using Python and Excel, ensuring clean and accurate data for reporting purposes. Collaborated with business stakeholders to define and deliver tailored reporting solutions that aligned with strategic business objectives.
Assisted in the implementation of ETL processes to integrate data from various internal systems into a centralized reporting platform.
Environment: Power BI, SQL Server, Python, Excel, SSRS.
Automated Pension & Benefits Distribution System May 2014 – Oct 2017
Software Engineer
Developed automated SQL queries and reports, reducing manual reporting time by 30%.
Contributed to the development of ad-hoc reports and dashboards, improving internal decision-making and reporting efficiency.
Assisted in the collection and processing of data from various business departments, ensuring alignment with reporting needs.
Wrote SQL queries for data extraction, transformation, and loading (ETL) from multiple data sources.
Supported the creation of dynamic reports and dashboards in Excel and Power BI, enabling managers to make data-driven decisions.
Conducted basic statistical analysis on customer feedback and performance data to identify trends and areas for improvement.
Environment: SQL Server, Excel, Power BI.
Projects & Achievements:
Spearheaded the automation of the customer behaviour analysis reporting process using SQL and Python scripts, saving 25% of time previously spent on manual report generation.
Resulted in faster turnaround time for reporting and more timely insights into customer trends.
Developed an interactive Power BI dashboard to track sales performance across different regions, providing real-time insights for senior management.
Built a customer insights dashboard in Power BI, combining data from Snowflake, SQL, and external APIs.
Integrated data from multiple sources (SQL Server, Snowflake,Azure, Excel), enabling stakeholders to track key metrics, trends, and KPIs. Analyzed energy distribution performance data and identified cost-saving opportunities, contributing to a 20% reduction in operational costs.
Utilized advanced statistical analysis and data modeling to identify inefficiencies in the energy distribution process. Developed and implemented automated ETL pipelines to integrate data from multiple platforms (SQL Server, Oracle, Excel) into Power BI for centralized reporting.
Reduced data preparation time by 35%, enhancing report accuracy and efficiency.
Created automated SQL queries and Power BI reports that allowed stakeholders to easily generate customized reports based on varying business parameters.
Improved decision-making by providing stakeholders with real-time data insights.
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