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Business Undestanding

Background

The Taste of the World Cafe debuted a new menu at the start of the year. So, the Data Analyst has been asked to dig into the customer data to see which menu items are doing well/not well and what the top customers seem to like best.

Role

Data Analyst for the Taste of the World Cafe

Objectives

• Explore the menu items table to get an idea of what's on the new menu.
• Explore the order details table to get an idea of the data that's been collected.
• Use both tables to understand how customers are reacting to the new menu.

Data Source

Data Playground at Maven Analytics (https://mavenanalytics.io/data-playground?order=date_added%2Cdesc&pageSize=10&search=resta)

Data Understanding

Dataset Information

Dataset Restaurant Order ini memiliki 2 table yang meliputi menu_items dan orders_details.

1. menu_items : 4 features with 32 records

Features	Distinct	Details
menu_item_id	32	131 - 132
item_name	32	Mac & Cheese, Meat Lasagna, Orange Chicken, Spaghetti & Meatballs, Steak Burrito, Pork Ramen, Steak Tacos, dll.
category	4	American, Mexican, Asian, Italian
price	14	$5 - $19.95

2. orders_details : 5 features with 12234 records

Features	Distinct	Details
orders_details_id	12234	1-12234
order_id	5370	1-5370
order_date	90	2023-01-01 to 2023-03-31
order_time	5010	10:50:46 to 23:05:24
item_id	32	101-132

Dataset Checking

1. Check Duplicat

  SELECT 
    od.orders_details_id,
    od.order_id,
    od.order_date,  -- Diperbaiki dari rder_date
    od.order_time,
    od.item_id, 
    COUNT(*) AS duplicate_count
FROM orders_details od
GROUP BY od.orders_details_id, od.order_id, od.order_date, od.order_time, od.item_id
HAVING COUNT(*) > 1;

Note

Tidak ada Duplikat.

2. Check Missing Value

  SELECT 
    SUM(CASE WHEN od.orders_details_id IS NULL THEN 1 ELSE 0 END) AS orders_details_id_missing,
    SUM(CASE WHEN od.order_id IS NULL THEN 1 ELSE 0 END) AS order_id_missing,
    SUM(CASE WHEN od.order_date IS NULL THEN 1 ELSE 0 END) AS order_date_missing,
    SUM(CASE WHEN od.order_time IS NULL THEN 1 ELSE 0 END) AS order_time_missing,
    SUM(CASE WHEN od.item_id IS NULL THEN 1 ELSE 0 END) AS item_id_missing
FROM orders_details od;

Note

Terdapat missing value pada item_id sebanyak 137 rows.

Business Insight

1. The most favored food by customers in this restaurant is Asian category, with around 3,470 orders. The Italian, Mexican, and American categories have similar order counts, around ~2,700+.

   

2. The Top 5 Best-Selling food items in this restaurant are Hamburger (American), Edamame (Asian), Korean Beef Bowl (Asian), Cheeseburger (American), and French Fries (American).

   

3. The Top 5 Worst-Selling food items in this restaurant are Chicken Tacos (Mexican), Potstickers (Asian), Cheese Lasagna (Italian), Steak Tacos (Mexican), and Cheese Quesadillas (Mexican).

   

4. The highest revenue is generated by the Korean Beef Bowl (Asian), with a total of $10,554.60. Other high-revenue items show only a slight difference in earnings.

   

5. The item with the lowest revenue is Chicken Tacos, generating $1,469.85, which is also the least ordered by customers.

6. Based on the seasonality analysis, consumer behavior can be observed. Customers at this restaurant particularly enjoy placing orders during lunchtime. As shown in the chart below, the peak order time occurs around 12 PM. Additionally, the second peak happens around 5 PM, just before dinner. However, customers are less inclined to order around 3 PM.

   

7. From a weekday perspective, customers at this restaurant prefer visiting on Mondays and Fridays, with peak times during lunch at 12 PM and just before dinner at 5 PM. However, the day with the highest customer turnout is Wednesday.

   Tableau.Public.-.Book5.2024-12-04.23-02-21.mp4

8. When analyzing orders by month, the highest number of orders occurred in January, while the lowest were observed in February. Upon a more detailed examination by hour, peak times consistently occur around 12 PM during lunch and 5 PM just before dinner throughout all months. When analyzing by weekdays, the peak days show some variation; however, Mondays and weekends are generally favored by customers.

   Tableau.Public.-.Book5.2024-12-04.23-15-21.mp4

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11. Here is the chart showing the order IDs with the highest total number of items purchased.

    output.compress-video-online.com.mp4

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