Project Details

AtliQ, a dynamic hardware company, is on an upward trajectory, offering diverse products to customers worldwide through multiple channels. From retail to direct sales and distributor networks, spanning online platforms to brick-and-mortar stores, our reach knows no bounds.

To fuel our expansion and steer strategic choices with precision, AtliQ is forging ahead with the establishment of a robust data analytics team.

● Established a Power BI dashboard with real world 1.8 million of data from 2 different sources (Excel & SQL database)
● The dashboard enabled Atliq hardware to analyze different department sales trends and make data-driven decisions, leading to a projected 10% revenue acceleration and 20% reduction in data-related expenses.

🎯 Power BI Key Technics:
⚪Data collection, Exploration, Transform & Load
⚪DAX, Power Query, Data Modeling, Visualization
⚪Bookmarks, Page navigation
⚪Embed link

Project video

Project Details

End-to-End FinTech Data Analytics Project: SQL, Python-ETL & Power BI
→ Analyzed transactional data for actionable insights. Source Data: CSV & SQL queries; Database: MySQL via DBeaver; ETL: Python; Visualization: Power BI.
→Key KPIs: Unique customers, month-wise transactions, regional customer distribution, transaction type analysis, monthly active customers, closing balances, 5-day deposits/withdrawals, interval analysis, weekly comparisons, and 15-day forecasts.

Process:
Phase 1: MySQL setup, data import, and Python ETL.
Phase 2: SQL-driven KPI analysis using joins, CTEs, and window functions.
Phase 3: Loaded data to Power BI via SQL.
Phase 4: Data modeling, custom measures, dynamic visuals, and time series analysis in Power BI.
Phase 5: Interactive dashboard deployed on the Power BI Web Service.

→ Outcome: Delivered a robust analytics solution; recommended addressing negative balances to enhance data integrity.

Project video

Project Details

1. Sensitivity Analysis & Forecasting
- Sales and Profit Margins Across Discount Scenarios
- Time Series Analysis

2.Region wise sales & profit Margin% of Product, Category, outlet, Sales-Man Wise Analysis

3. Profit Margin Breakdown by Region, Category & Discount

4. Sales & Profit Margin % Analysis
- Total Sales and Average Profit% by Region & Channel
- Top 5 & Lowest 5 Product, Sales Man and Store Name by Sales & Profit%

5. Customer Rating Analysis
- Customer Satisfaction Trends by Product Category
- Yearly Rating Analysis by Product Category
- Store-Wise Rating Comparison Against Overall Average
- Sales & Profit Insights for Products Rated Below 3
- Total Sales by rating High-Low

6. Growth & Discount Analysis
- MoM : Sales for Same store
- YoY : Growth for Same Store
- YoY: Sales Growth by Customer Rating
- Discount Impact on Sales and Profit Margins by Product Category

Project video