Sales Insights FMCG Data Analysis
Video Demo
Tools & Technology
SQL
Power BI
Excel
Results: Insights
- Total Revenue started trending down on Thursday, September 1, 2022, falling by 40.84% (10.16 million INR) in 273 days.
- Total Revenue dropped from 34.75 million INR to 30.1 million INR during its steepest decline between Tuesday, June 1, 2021, and Wednesday, September 1, 2021.
- Total Revenue experienced the longest period of decline (-10.16 million INR) between Thursday, September 1, 2022, and Thursday, June 1, 2023.
- Profit Margin % started trending down on Thursday, December 1, 2022, falling by 26.23% (0.46%) in 182 days.
- Profit Margin % dropped from 1.75% to 1.29% during its steepest decline between Thursday, December 1, 2022, and Thursday, June 1, 2023.
- Profit Margin % experienced the longest period of decline (-0.46) between Thursday, December 1, 2022, and Thursday, June 1, 2023.
Problem Statement
- AtliQ Hardware is a company that supplies computer hardware and peripherals to many clients across India. AtliQ Hardware's head office is situated in Delhi, India & and they have many regional offices throughout India.
- The sales director is facing issues in terms of tracking the sales in this dynamically growing market & and he is having issues with the growth of this business, as overall sales were declining. The company has a regional manager for North India, South, and Central India. Whenever he wants to get insights from any of these regions he would call these people & and get some insights on the phone that this was the sales last quarter and we are growing by this much in the next quarter.
- The problem is that all these things happen in verbal form & and there is no proof with facts of how his business is affected. He wants to make data-driven decisions to increase sales of his company.
- He wants a simple data visualization tool that he can access daily. By using tools and technologies one can make data-driven decisions that help in increasing the sales of the company.
Data Validation Using MySQL
- Ensuring data quality and integrity.
- Verified all records in customer, date, markets, products, and transactions tables for completeness and accuracy.
- Checked garbage values or outliers in the sales amount column of the transaction table and marked them.
- Checked for blank or null values in any of the tables and marked them as missing.
- Checked transactions that have a currency other than INR and converted them to INR using the exchange rate.
Data Cleaning and Transformation(ETL) using PowerBI
- Performed data cleaning and transformation to prepare the data for analysis.
- Removed all records with blank or null values in any of the columns.
- Removed records with product codes greater than Prod279, as they are outliers or errors.
- Standardized the sales amount column by adding another column with converted USD values to INR using the exchange rate.
- Removed duplicate records based on the primary key or a combination of columns.
Data Analysis Using MySQL
- Performed analysis to extract insights from the transaction and date tables.
- Joined the transaction and date tables using an inner join and applied filters by year, market, month, and currency to select the relevant data.
- Calculated the total sales amount, number of transactions, and other metrics of interest using aggregation functions.
Data Visualization using Power BI
- Performed data visualization using Power BI to create interactive and insightful reports and dashboards.
- Created DAX measures to define custom calculations and metrics for the data.
- Created various line, bar, and column charts to visualize the data and compare different categories and trends.
- Create year and month slicers to filter the data and enable dynamic analysis.