Best of my skills
Aniket Parida
Data Analyst
Bangalore
Summary
I am Data Analyst Engineer with strong expertise in Python, SQL, Power BI, Tableau, Advanced Excel, and pandas, specializing in transforming raw, complex datasets into actionable business insights. Proficient in SQL for efficient data extraction, querying, and optimization, and skilled in Python and pandas for advanced data cleaning, exploratory analysis, and automation of analytical workflows. Demonstrates strong capability in Excel for rapid reporting, data modeling, and validation.
Experienced in developing interactive dashboards and data visualizations using Power BI and Tableau to support strategic decision-making. Adept at identifying trends, uncovering patterns, and solving complex business problems through data-driven analysis. Possesses a strong understanding of data integrity, performance optimization, and analytical best practices, enabling effective collaboration across teams and delivering measurable business value across diverse industries.
Overview
1
1
year of professional experience
2
2
Languages
Work History
Data Engineer
Besant Technologies
02.2026 - Current
- I worked as a Data Analyst on an e-commerce analytics project focused on transforming large volumes of transactional, customer, and product data into actionable business insights. The project involved analyzing end-to-end customer journeys, sales performance, inventory movement, and marketing effectiveness to support data-driven decision-making.
- SQL was extensively used for data extraction, cleaning, and transformation from relational databases. I designed optimized queries, complex joins, CTEs, and aggregations to create analytical datasets for reporting. These datasets were structured to track key e-commerce KPIs such as revenue growth, conversion rates, average order value, customer retention, and product-level performance.
- Power BI was used to build interactive dashboards and reports for business stakeholders. I developed dynamic visuals, DAX measures, and drill-through reports that enabled users to analyze trends by time, region, category, and customer segment. These dashboards helped leadership monitor daily sales performance, identify high-performing products, and detect revenue drop-offs early.
- Azure Data Factory pipelines were implemented to automate data ingestion and transformation workflows. I built scheduled pipelines to pull data from multiple sources, apply transformations, and load curated data into analytical storage for reporting. This automation reduced manual effort, improved data freshness, and ensured consistency across reports.Overall, the project demonstrated my ability to work across the full analytics lifecycle—from data engineering and automation to visualization and business insight generation—within a fast-paced e-commerce environment.
Data Analyst
Basant Technology
11.2025 - 01.2026
- This shopping company data analytics project focused on analyzing sales performance and customer behavior by transforming raw operational data into actionable business insights. The project involved working with transactional, product, and customer datasets stored across multiple sources, requiring efficient extraction, cleaning, and integration.
- Using MySQL, I queried and cleaned data from multiple tables by applying joins, filters, aggregations, and subqueries to prepare structured datasets for analysis. Key metrics such as total sales, order frequency, product-wise revenue, and regional performance were derived to support business reporting.
- Python played a critical role in data preprocessing and analysis. With Pandas, I handled missing values, removed duplicates, standardized data formats, and performed exploratory data analysis. Matplotlib was used to visualize sales trends, seasonal patterns, and customer purchasing behavior, helping identify growth opportunities and anomalies in the data.
- To automate and scale data workflows, Azure Data Factory pipelines were implemented for data ingestion and transformation, ensuring consistent and timely data availability for analysis. All scripts, SQL queries, and analysis workflows were maintained using Git, enabling version control and reproducibility.
- Overall, the project strengthened my skills in end-to-end data analytics, ETL pipeline development, visualization, and insight generation, supporting data-driven decision-making within a shopping company environment.
Data Analyst
Besant Technologies
09.2025 - 10.2025
- This e-commerce analytics project focused on transforming raw, fragmented datasets into reliable, analysis-ready data to generate meaningful business insights. My primary responsibility involved data cleaning, transformation, and integration across multiple data sources, ensuring high data accuracy, consistency, and usability throughout the analytics lifecycle. The datasets included common e-commerce challenges such as missing values, duplicate records, inconsistent formats, and data quality issues that required systematic preprocessing.
- Using SQL, I extracted and joined data from transactional, customer, and product tables, applying aggregations and filters to create structured analytical datasets. Python, along with Pandas, was used extensively for data cleaning, handling null values, removing duplicates, standardizing columns, and performing feature engineering. I implemented data validation checks to improve data reliability and reduce errors in downstream analysis.
- For exploratory data analysis, I used Matplotlib to visualize sales trends, customer behavior patterns, and product performance over time. These visual insights helped identify seasonality, outliers, and revenue-driving products.
- All code, queries, and analysis workflows were managed using Git, ensuring version control, collaboration readiness, and reproducibility. The cleaned and integrated datasets formed a strong foundation for advanced analysis and reporting, strengthening my skills in ETL workflows, data analysis, and best practices for scalable e-commerce analytics.
Data Analyst Intern
Besant Technology
08.2025 - 09.2025
- In this Sales Performance Analysis project, I worked as a Data Analyst to evaluate and improve business outcomes for a retail organization using Excel, SQL, and Power BI. The project began with cleaning and preparing raw retail datasets, including sales, customer, and product data, using Excel. Advanced Excel features such as VLOOKUP, PivotTables, conditional formulas, and Power Query were applied to ensure data accuracy, consistency, and usability.
- The cleaned data was then stored in a SQL database, where I performed joins, aggregations, and optimized queries to calculate key metrics such as total revenue, top-selling products, regional sales performance, and monthly trends. These queries formed the foundation for analytical reporting.
- Power BI was used to create interactive dashboards and visual reports. I designed KPIs and visuals to track revenue growth, sales by region, and product performance, enabling stakeholders to quickly identify trends and make informed, data-driven decisions in a competitive retail environment.
Education
Mechanical Engineering -
Srinix College of Engineering
Balasore, Odisha01.2024
Skills
Python
Advance Excel
Pandas
SQL
Power BI
Tableau
Numpy
Matplotlib
MySQL
Git
Azure
AWS
Software
Interests
Trading, Games, Music
Timeline
Data Engineer
Besant Technologies
02.2026 - Current
Data Analyst
Basant Technology
11.2025 - 01.2026
Data Analyst
Besant Technologies
09.2025 - 10.2025
Data Analyst Intern
Besant Technology
08.2025 - 09.2025
Mechanical Engineering -
Srinix College of Engineering