SHIVANVITHA NARALA

• Worked closely with clients and business teams to clarify project needs and customizations, ensuring clear communication and effective collaboration.
• Developed and maintained applications using Unix, shell scripting, and SQL databases including Oracle, MySQL, and Teradata. Implemented Splunk for enhanced data visibility and governance.
• Automated the delivery of real-time reports to client dashboards, incorporating data from diverse sources such as Azure Databricks and Cloudera for a comprehensive historical data view.
• Authored and optimized complex SQL queries, managing large-scale databases to improve data retrieval and operational efficiency.
• Leveraged Tableau to craft engaging, dynamic visualizations and dashboards that provide insightful views into client data, pushing the boundaries of Tableau’s visualization capabilities.
• Utilized advanced Excel features to construct pivot tables and reports, enhancing interactive data presentations and dashboard creation.
• Built and updated interactive dashboards using Power BI and Tableau, focusing on delivering actionable insights in marketing and e-commerce.
• Performed targeted data analyses to uncover patterns and insights, using Python to handle complex data sets effectively.
• Engaged in the design and deployment of data reports across platforms like Excel and Power BI, focusing on integrating multiple data sources for enriched analytics.
• Improved project transparency and client interaction by managing communications and updates through Jira, ensuring stakeholders are always informed.

Environment: Unix, Shell Scripting, Oracle, MySQL, Teradata, Splunk, Azure Databricks, Cloudera, SQL, Tableau, Excel, Power BI, Python, Jira.

• Improved health data processing by using SQL and Python, speeding up result generation by 46% and reducing manual workload by 4 hours weekly.
• Built KPI-driven Tableau dashboards that improved stakeholder decision-making by 40%, enhancing marketing and e-commerce analytics.
• Managed daily, weekly, and monthly metric updates using AWS Redshift and integrated data from diverse sources, including Teradata and Oracle, to ensure accuracy and completeness.
• Identified inefficiencies and implemented cost-saving strategies through Tableau, achieving savings of $2.1 million.
• Designed SQL and Tableau reports, dashboards, and scorecards that improved operational decisions by 56%, incorporating data visualization techniques and analytical problem-solving.
• Streamlined data import, cleaning, and analysis using SQL, Hive, and enhanced these processes with Excel Macros for efficiency.
• Developed comprehensive data models using Erwin and enhanced database interactions using Oracle PL/SQL, ensuring robust data governance.
• Conducted extensive data analysis using SQL, Python, and Excel, applying SAS for deeper insights into transactional systems.
• Created interactive and user-friendly dashboards on Tableau Server, allowing end users to access data easily and make on-demand decisions.
• Recommended and implemented improvements for data consistency and efficiency, using Cloudera and Azure Databricks to manage and visualize data effectively.

Environment: SQL, Python, Tableau, AWS Redshift, Teradata, Oracle, Excel Macros, Hive, Erwin, Oracle PL/SQL, SAS, Cloudera, Azure Databricks.

• Worked closely with product, technology, finance, and marketing teams to gather business requirements, using agile methodology to guide the product development life cycle.
• Developed and optimized SQL queries for databases including Oracle, SQL Server, and Teradata; utilized SQL Server Integration Services (SSIS) and Cloudera for efficient data migration and warehousing.
• Performed comprehensive data analysis using Python and SAS, ensuring data quality through rigorous acquisition, profiling, and validation processes.
• Created and managed dynamic dashboards and reports in Tableau and Power BI, incorporating insights from various data sources to support marketing and e-commerce analytics.
• Employed advanced Excel functions like PivotTables, VLOOKUPs, and Power Query for data cleansing, playing a key role in data governance and accuracy.
• Applied statistical techniques using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn for exploratory data analysis, summarizing key characteristics of large data sets.
• Transformed complex data into actionable insights by predicting future outcomes with SQL, facilitating effective stakeholder communication and decision-making.
• Designed interactive storytelling dashboards on Tableau Server, enabling end users to access and understand data instantly, enhancing user engagement and information accessibility.

Environment: Agile methodology, Oracle, SQL Server, Teradata, SQL Server Integration Services (SSIS), Cloudera, Python, SAS, Tableau, Power BI, Excel (including PivotTables, VLOOKUPs, Power Query), Pandas, NumPy, Matplotlib, Seaborn.