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https://github.com/bhavanachitragar/blinkit-analytics
This project involves creating interactive dashboards to analyze sales data over a decade. The dashboard focuses on items types, displaying key metrics like total sales, sales trends by year, fat content distribution, and location type.
https://github.com/bhavanachitragar/blinkit-analytics
dax-expression powerbi-report
Last synced: about 12 hours ago
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This project involves creating interactive dashboards to analyze sales data over a decade. The dashboard focuses on items types, displaying key metrics like total sales, sales trends by year, fat content distribution, and location type.
- Host: GitHub
- URL: https://github.com/bhavanachitragar/blinkit-analytics
- Owner: bhavanachitragar
- Created: 2024-07-30T07:34:04.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-07-30T07:57:51.000Z (4 months ago)
- Last Synced: 2024-07-30T10:52:13.000Z (4 months ago)
- Topics: dax-expression, powerbi-report
- Homepage: https://app.powerbi.com/groups/me/reports/2292d629-9a35-42fd-926b-c67e21e6a168/0345e338001793c1e6a6?ctid=41c6f93d-ac26-4f3b-90df-338b4c94dec5&experience=power-bi&bookmarkGuid=ff091c035bec2df45422
- Size: 1.18 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Blinkit Analytics Dashboard using PowerBi
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This project involves creating interactive dashboards to analyze sales data over a decade. The dashboard focuses on dairy items, displaying key metrics like total sales, sales trends by year, fat content distribution, and location type. It provides a comprehensive overview of all item types, highlighting total sales, sales trends, item ranking by sales, and similar distribution metrics for fat content and location types. These dashboards facilitate data-driven decision-making by providing clear visual representations of sales performance and item distribution. The project aims to help stakeholders understand market trends and optimize inventory management.
## Steps Involved:
### 1. Cleaning Data
- Removing unnecessary columns and duplicates.
- Handling missing values.
- Changing data types as needed.
### 2. Data Analysis
- Used DAX functions, measures, and calculated columns to perform detailed analysis.
### 3. Mertics
1. The total number of sales transactions made is 1.20M Sales.
2. The average customer rating out of 5 is 3.92.
3. The total number of items available for sale is 9K.
### 4. Insights:
- Fruits and Vegetables has the highest sales of 178K.
- Snack Foods has 173K sales is second highest.
- In YOY chart 2020 (peak year) has sale of 295K.
- The pie chart divides the sales based on the location type:
1. Tier 1: 28.05%
2. Tier 2: 39.77%
3. Tier 3: 32.18%
#### Sanpshots:
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