Data Analyst Power Bi

Chandana Kanukollu

551-***-**** *********.**.**@*****.*** LinkedIn Github

PROFESSIONAL SUMMARY

• Analytical and detail-oriented Data Analyst with 2.5 years of experience transforming raw data into actionable insights across healthcare, finance, and marketing domains. Proficient in SQL, Python, Tableau, and ETL workflows to automate reports and optimize decision-making.

• Skilled in developing data solutions in Agile environments, including automated pipelines, data models, and interactive dashboards to support business goals.

• Passionate about ensuring data accuracy and improving analytics workflows through strong attention to detail, hands-on Excel/SQL experience, and cross-functional collaboration.

• Experienced in transforming complex healthcare and marketing data into reliable dashboards, forecasts, and automated reports, using ETL and Power BI.

• Now aiming to contribute my expertise in a dynamic role focused on building data infrastructure and delivering impactful analytics solutions.

EDUCATION

Master of Science in Management Information Systems May 2025 Stevens Institute of Technology, Hoboken, New Jersey TECHNICAL SKILLS

Data Management & Databases MySQL Workbench, PostgreSQL, Azure Data Studio (Basic familiarity). Data Analysis & BI Tools SQL, Excel, Power BI, Tableau, Qlik Sense (Basic), SAP Analytics Cloud (SAC), Customer Success Tools (Planhat - Basic familiarity), Microsoft Office Suite (Word, PowerPoint, Outlook), Microsoft OneNote, SharePoint Programming & Data Engineering Python, R, PySpark, Talend Open Studio, DBeaver Big Data & Cloud Technologies Databricks, Apache Spark, Delta Lake (Basic Knowledge). Project & Process Management Agile Methodology, Business Strategy, Stakeholder Engagement, Cross-Functional Collaboration, Decision-Making

CERTIFICATIONS

• Associate Data Engineer Certification – Databricks

Advanced Software Engineering – Global Tech Walmart PROFESSIONAL EXPERIENCE

Associate Data Analyst - Artha Solutions, Hyderabad, Telangana, India September 2022 - July 2023 Client: Commonwealth Care Alliance (CCA), MA

Project: Encounter Data Management & Reporting for MassHealth

• Assisted in writing SQL scripts using predefined business rules and expression terms (e.g., encounter type, service code validations, date range checks) to support the preparation of monthly encounter data submissions for MassHealth.

Supported data quality checks across 100K+ records, including format validation like field length, data type, record-level de-duplication, and completeness verification for audit and compliance.

Participated in data cleansing tasks in Talend Open Studio, working with senior developers to process input files in CSV, Excel, and API formats (validating file layouts, standardizing column headers, normalizing codes), reducing manual cleanup time by 25–30%.

Used Talend jobs configured by senior developers and performed daily QA routines to verify data loading, cleansing, and transformation (e.g., reviewing job logs, checking rejected rows, comparing pre/post row counts), maintaining high ETL accuracy with <2% data rejection rate.

Built and contributed to KPI-focused Tableau dashboards, using MDX and SQL to provide real-time visibility into data accuracy, submission timeliness, and audit readiness.

Built basic Tableau visualizations and formatted to existing dashboards by adding filters, updating views, and formatting charts to support compliance teams improve usability for non-technical users.

Participated in POC (Proof of Concept) tasks using Python, including basic anomaly detection and trend exploration on test datasets like flagging missing records, identifying irregular volume spikes to support future automation.

Developed Excel-based reconciliation templates, reducing submission errors during pre-validation and improving internal audit and submitted weekly data validation logs.

Referred to mapping documents and validation document to ensure traceability across data sources and ETL transformations (like field-to-field logic, source-to-target mapping) during development and QA activities.

Supported unit testing of SQL logic and Talend jobs by reviewing outputs against expected results before deployment to QA or production environments.

Worked in Agile/Scrum teams with BI developers, QA teams, and business stakeholders—participating in daily stand-ups, sprint review meetings, and requirement walkthroughs—to deliver actionable insights and ensure timely, compliant data reporting in line with SDLC best practices. Used Jira to manage user stories, update sprint status, and support task tracking throughout the development lifecycle. Customer Insight & Engagement Analytics Platform March 2021 – August 2022

Automated Supported the automation of data wrangling for 50K+ customer records using Python (e.g., missing value handling, date formatting, and category normalization), improving trend analysis workflows by 35% and reducing manual effort for marketing teams.

Assisted in designing MySQL databases and contributed to Tableau dashboards to visualize user engagement (e.g., click-through rates, session duration, campaign interaction), helping CRM teams monitor performance in real-time and leading to a 15% boost in response rates.

Helped develop ETL workflows using Talend Open Studio and DBeaver (e.g., scheduling data pulls, merging datasets, filtering invalid entries) to streamline multi-source reporting and improve delivery speed by 40%.

Collaborated with BI developers and business analysts to improve dashboard usability and data consistency (e.g., aligning KPIs, standardizing field names, adding dynamic filters), which enhanced cross-functional collaboration and reporting accuracy.

ACADEMIC PROJECTS

Kidney Disease Prediction Using Machine Learning January 2024 – May 2024

• Developed a machine learning model to predict diabetes using diagnostic data from 768 patients. Applied Logistic Regression, SVM, and Random Forest algorithms—achieving the best performance with Random Forest at 84% accuracy and 84.05% ROC-AUC. Through feature analysis, we identified glucose and BMI as key indicators of diabetes.

• The model enabled early risk detection in 40% of cases, helping to inform targeted clinical interventions and reduce potential healthcare costs. The project demonstrated how predictive modeling can support real-time diagnosis and improve outcomes in clinical settings. Delivered a final project presentation to faculty leadership, demonstrating predictive insights and actionable recommendations from healthcare ML models. Monroe County Traffic Crash Analysis & Safety Insights August 2023 - December 2023

• We analyzed 48,316 crash records in Monroe County, New York. Using Power BI, we identified clear contributing factors in approximately 40% of the incidents, primarily through top 10 accident causes and informing the development of targeted driver safety interventions.

• Based on trend analysis, our insights are projected to reduce peak-day crashes by up to 15%, particularly on Fridays, which showed the highest crash volume.

ACTIVITIES

Software Development Program, Stevens Institute of Technology Jan 2024

• Organized a 48-hour hackathon event, coordinating logistics, securing sponsorships, assembling a panel of industry expert judges, and managing over 200 participants.

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