Create Order queries.md

Author: deva-246

Order Based Business queries/Order queries.md

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+## Order based Business Queries and solutions
+### 1. Count of unique number of orders that are placed ?
+
+ ![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/9bfec0ac-9970-4719-8314-166057b0e2b6)
+ 
+ **95 unique orders** are placed according to this dataset.
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+ 
+ 
+
+### 2. At what modes of rain were orders placed?
+
+ ![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/0192b30f-7201-4c39-ba72-2484f4c87ec8)
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+ There are 3 modes namely -**Heavy,moderate,drizzle** with 0,2 and 5 as it's respective identifiers from the dataset.
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+ 
+ 
+
+### 3. What are the uniqiue restaurent names from the overall orders that have been placed?
+
+ ![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/f290ab7c-7a34-48b9-9345-321b54263034)
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+ There are **49** unique restaurents name present in the order history in the given dataset.
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+ 
+ 
+
+### 4. Which Restaurent holds most of the orders ?
+
+![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/68b8cc0d-8b06-4f95-a608-2d278e46eb83)
+ 
+![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/e4b61785-5daf-4261-a905-cd880b58fdc0)
+
+![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/377aba1b-8f0a-43b6-8dd6-61ceb4b9dfd1)
+ 
+![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/5e8a17f7-f73e-4437-bfcb-68f3379d41bc)
+ 
+
+**The Bowl company** is the restaurent which holds the highest number of orders according to the swiggy customers present in the dataset. from the above results we can also categorize the restaurents as **most favourite , favourite and least favourite** by which required recommendations can be activated by the company to attract its customer to place an order. 
+
+### 5. List out the orders count in the form of Month and Year combination?
+
+![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/07a340db-af98-4a2b-b1ed-370f302695cc)
+
+![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/3ae3ecd2-5df7-40d0-8e0a-53bfd2b67cb0)
+
+From the above result, **2021, October** holds the highest number of Orders.
+
+### 6. What is the revenue earned by swiggy on each month ?
+
+![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/7d15f49e-9eca-4312-a6d1-a182a6ee8205)
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+From the above results we can conclude that **October** month has generated the highest revenue and **March** month has generated least revenue, considering this more discounts and offers can be included during the least revenue months to bosst up the sales.
+
+### 7. What is the average order value ?
+
+![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/e61fa810-dd50-4af1-b213-cd38ccaf4194)
+
+### 8. Revenue based difference ?
+
+![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/b88832df-f7b2-4b7c-aecf-0bb03b1c4b97)
+
+![image](https://github.com/deva-246/DataAnalysis-on-Realtime-Swiggydata-using-SQL/assets/75877347/7219a3d9-c8da-42a9-bf8d-fdbafbf44a89)
+