Narendra K
Professional Summary
Results-driven BCA graduate and aspiring Data Analyst with hands-on experience in Python, SQL, Power BI, Power Query and Excel. Built end-to-end analytics solutions — data ingestion, cleaning, transformation, interactive dashboards and a predictive churn model achieving ~80% accuracy. Delivered reusable data cleaning pipelines that reduced data errors by ~95% and automated report refreshes to accelerate time-to-insight. Seeking a Data Analyst role in Bengaluru to contribute analytical skills, dashboarding expertise and process automation to a data-driven team.
Technical Skills
Work Experience
- Cleaned, normalized and pre-processed business datasets using Pandas, Excel and Power Query to prepare reliable inputs for reporting and analysis; implemented validation checks to catch inconsistencies early.
- Authored optimized SQL queries (JOINs, aggregations and window functions) to extract and aggregate data for dashboards and ad-hoc stakeholder requests, improving analyst efficiency.
- Designed and iterated interactive Power BI dashboards with DAX measures, KPI cards and dynamic slicers to visualize sales and operational KPIs and support decision-making.
- Automated recurring ETL tasks and data refreshes using Power Query and Python scripts, reducing manual preparation time and enabling more frequent report updates.
- Performed data validation and discrepancy analysis in Excel and SQL to ensure accuracy of deliverables used in monthly business reviews and management reports.
- Collaborated with mentors and stakeholders to translate business requirements into analytics specifications, documented transformation logic and delivered handover materials for continuity.
Projects
- Designed an interactive Power BI dashboard to analyse sales trends, regional performance and customer behaviour across multiple product categories from a 50,000+ row retail dataset.
- Wrote optimized SQL queries using JOINs, CTEs and window functions to extract and aggregate data for visualization and KPI calculations.
- Reduced report generation time by 40% by automating data refresh using Power Query connections and reusable dataflows.
- Implemented 6 dynamic slicers and KPI cards for real-time filtering by region, product category and date range to enable data-driven decisions.
- Created custom DAX measures to calculate year-over-year growth (15% increase) and quarter-on-quarter trends, with conditional formatting for quick insights.
- Cleaned and restructured three raw datasets (10,000+ rows each) using Excel formulas, Power Query and SQL functions to prepare high-quality analytical inputs.
- Standardised inconsistent date formats, resolved duplicate records and filled missing values using domain logic and SQL window functions.
- Reduced data errors by 95% through systematic transformation steps and created reusable Power Query templates for future imports.
- Identified and resolved 2,450+ duplicate records and 3,800+ missing values using Excel VLOOKUP, conditional formulas and SQL deduplication methods.
- Built comprehensive data cleaning documentation with step-by-step transformation logic and validation checks to support team knowledge transfer.
Education
Certifications
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