Experienced Data Analyst with 4+ years of turning complex data into clear, actionable insights for business growth. Skilled in SQL, Power BI, Tableau, Power Query, Pivot Tables, Power Pivot, Advanced Excel, Snowflake, R,…
Experienced Data Analyst with 4+ years of turning complex data into clear, actionable insights for business growth. Skilled in SQL, Power BI, Tableau, Power Query, Pivot Tables, Power Pivot, Advanced Excel, Snowflake, R, and Databricks. Proven track record in building dashboards, analyzing trends, and solving business problems across inventory, SLA, performance, and cash flow. Strong at data storytelling, stakeholder collaboration, and driving decisions through meaningful reports and automation.
Designed and maintained inventory tracking metrics utilizing Tableau which track the incoming volume, throughput, and closed cases defined timeframes enabling operational teams to proactively identify bottlenecks and optimize resource allocations.
Collaborated with the Ops Team to create associate's performance metrics based on their work item per hour using tableau and streaming data sources involving complex SQL scripting, visualization, parameters, filter actions, and calculated fields.
Provided deep drill-down features in a complex dashboard in helping the enterprise business users to view underlying data of metrics calculations.
Created daily ops reports with key demand metrics for executive leadership, optimizing business decisions.
Developed automated SQL reports embedding time-series analysis to track SLA targets with real-time visibility into associate activity which eliminated manual monitoring.
Conducted in-depth cleansing & wrangling of JSON datasets, decluttered them to achieve 99% accuracy.
Worked with principal DAs to test and validate the data migration after new fields and tables were pushed into production.
Discovered and resolved a critical data issue in a production table, preventing potential data loss by collaborating with the data warehouse team before impacting the operations.
Designed and maintained inventory tracking metrics utilizing Tableau, Collaborated with the Ops Team to create associate's performance metrics, Provided deep drill-down features in a complex dashboard, Created daily ops reports for executive leadership, Developed automated SQL reports embedding time-series analysis, Conducted data cleansing & wrangling of JSON datasets, Discovered and resolved a critical data issue in a production table
Effectively integrated with business analysts and data modelers to define data mapping documents and design processes for various sources and targets.
Created high-efficiency tableau scorecards, dashboards using stacked bars, geographical maps, and gann charts using Show Me functionality
Coordinated data migration from the legacy vendor system to a new vendor, managing large datasets and enhancing reporting capabilities for Tableau dashboards.
Comprehensive reports Visualization using graphs in Google Sheets to convey insights for client's presentations.
Collaborated with cross-functional teams in stakeholder meetings to refine project requirements, and align goals resulting in a 30% increase in successful project deliverables.
Utilized R for data analysis & visualization, to improve decision-making using data-driven insights.
Integrated with business analysts and data modelers to define data mapping documents, Created high-efficiency tableau scorecards and dashboards, Coordinated data migration from legacy vendor system, Comprehensive reports visualization in Google Sheets, Collaborated with cross-functional teams in stakeholder meetings
Worked on the project to build predictive modeling using the provided customer dataset to identify the customer churn rate of an enterprise-level sample dataset from Kaggle aiming to reduce the churn rate.
Used R to perform minimal data cleaning and applied machine learning algorithms such as logistic regression and random forest to predict the churn rate
Utilized Tableau desktop to create a visualization of churn rate, high-risk vs low-risk customers, aging of customer subscription impact, etc.
Optimized the model parameters and reduced the prediction errors by 12%.
Engaged with group members to research, analyze, & present the insight findings to the professor.
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