Supply Chain Analytics in Tableau or Power BI
Test your BI skills on a real-world dataset focusing on supply chain analytics. As the main data analyst for Just In Time, you will help solve key shipment and inventory management challenges, analyze supply chain inefficiencies, and create insightful dashboards to inform business stakeholders about potential problems and propose structural business improvements.
Be creative and make use of your full skillset! Use this Workspace to prepare your data, import the tables into your local Tableau or Power BI instance, and share your insights below.
The end goal will be a (set of) interactive dashboards that demonstrate clear insights for Just In Time.
💾 The data
|Customer||Customer ID||orders_and_shipments.csv||Unique customer identification|
|Customer||Customer Market||orders_and_shipments.csv||Geographic grouping of customer countries, with values such as Europe, LATAM, Pacific Asia, etc.|
|Customer||Customer Region||orders_and_shipments.csv||Geographic grouping of customer countries, with values such as Northern Europe, Western Europe, etc.|
|Customer||Customer Country||orders_and_shipments.csv||Customer's country|
|Order info||Order ID||orders_and_shipments.csv||Unique Order identification. Order groups one or multiple Order Items|
|Order info||Order Item ID||orders_and_shipments.csv||Unique Order Item identification. Order Item always belong to just one Order|
|Order info||Order Year||orders_and_shipments.csv||Year of the order|
|Order information||Order Month||orders_and_shipments.csv||Month of the order|
|Order information||Order Day||orders_and_shipments.csv||Day of the order|
|Order information||Order Time||orders_and_shipments.csv||Timestamp of the order in UTC|
|Order information||Order Quantity||orders_and_shipments.csv||The amount of items that were ordered within a given Order Item (1 record of the data)|
|Product||Product Department||orders_and_shipments.csv||Product grouping into categories such as Fitness, Golf, Pet Shop, etc.|
|Product||Product Category||orders_and_shipments.csv||Product grouping into categories such as Sporting Goods, Women's Apparel, etc.|
|Product||Product Name||orders_and_shipments.csv||The name of the purchased product|
|Sales||Gross Sales||orders_and_shipments.csv||Revenue before discounts generated by the sales of the Order Item (1 record of the data)|
|Sales||Discount %||orders_and_shipments.csv||Discount % applied on the catalog price|
|Sales||Profit||orders_and_shipments.csv||Profit generated by the sales of the Order Item (1 record of data)|
|Shipment information||Shipment Year||orders_and_shipments.csv||Year of the shipment|
|Shipment information||Shipment Month||orders_and_shipments.csv||Month of the shipment|
|Shipment information||Shipment Day||orders_and_shipments.csv||Day of the shipment|
|Shipment information||Shipment Mode||orders_and_shipments.csv||Information on how the shipment has been dispatched, with values as First Class, Same Day, Second Class, etc.|
|Shipment information||Shipment Days - Scheduled||orders_and_shipments.csv||Information on typical amount of days needed to dispatch the goods from the moment the order has been placed|
|Warehouse||Warehouse Country||orders_and_shipments.csv||Country of the warehouse that has fulfilled this order, the only two values being Puerto Rico and USA|
|Inventory & Fulfillment||Warehouse Inventory||inventory.csv||The monthly level of inventory of a product, e.g. 930 units|
|Inventory & Fulfillment||Inventory cost per unit||inventory.csv||The monthly storage cost per unit of inventory, e.g. $2.07|
|Inventory & Fulfillment||Warehouse Order fulfillment (days)||fulfillment.csv||The average amount of days it takes to refill stock if inventory drops below zero|
The data can be downloaded from the sidebar on the left (under Files).
Using either Tableau or Power BI, create an interactive dashboard to summarize your research. Things to consider:
- Use this Workspace to prepare your data (optional).
- Some ideas to get you started: visualize how shipments are delayed, by country, product, and over time. Analyze products by their supply versus demand ratio. Rank products by over or understock. Don't feel limited by these, you're encouraged to use your skills to consolidate as much information as possible.
- Create a screenshot of your (main) Tableau or Power BI dashboard, and paste that into the designated field.
- Summarize your findings in an executive summary.
STEP 1: DATA PREPARATION AND INITIAL DATA EXPLORATION
import pandas as pd data1 = pd.read_csv("data/orders_and_shipments.csv") data1.isnull().sum()
data2 = pd.read_csv("data/inventory.csv") data2.isnull().sum()
# Stats of data1 data1.describe()
# Combine order year, month, and day into order_Date # Convert order year, month, and day to string data1['Order Year'] = data1[' Order Year '].astype(str) data1[' Order Month '] = data1[' Order Month '].astype(str) data1[' Order Day '] = data1[' Order Day '].astype(str) # Combine order year, month, and day into order_Date data1['order_Date'] = data1['Order Year'] + '-' + data1[' Order Month '] + '-' + data1[' Order Day '] # Display the updated dataframe data1.head()
# Convert Order Time to string data1['Order Time'] = data1['Order Time'].astype(str) # Combine Order Year, Order Month, and Order Day into Order_Date data1['Order_Date'] = data1['Order Year'].astype(str) + '-' + data1[' Order Month '] + '-' + data1[' Order Day '] # Combine Shipment Month, Shipment Day, and Shipment Year into Shipment_Date data1['Shipment_Date'] = data1['Shipment Month'].astype(str) + '-' + data1['Shipment Day'].astype(str) + '-' + data1['Shipment Year'].astype(str) data1.head()
# Export data1 to CSV data1.to_csv('data2.csv', index=False)
There are no missing data. So the data can be used for data visualization.
STEP 2: DATA VISUALIZATION
✅ Checklist before publishing
- If you use Tableau, don't forget to publish your Tableau dashboard, make it available on Tableau Public and share the link.
- If you use Power BI, upload your
.pbixfile to this Workspace through the sidebar on the left (under Files).
- Remove redundant text cells like the background, data, challenge, and checklist. You can add cells if necessary.
✍️ Judging criteria
🧾 Executive summary
In a couple of lines, write your main findings here.
📷 Dashboard screenshot
Paste one screenshot of your Tableau or Power BI dashboard here.
🌐 Upload your dashboard
For Tableau: paste the link to your Tableau Public dashboard here.
For Power BI: upload your
.pbix file to Files in the sidebar on the left.