Using SQL to manipulate and clean the data, analyzing to discover trends and patterns, dig insights in an understandable format.

The fields present in Items dataset are,

 1. id 2. Order_id 3. Name 4. Is_veg/not 

The fields present in Orders dataset are,

 1. id 2. order_id 3. order_Total 4. restaurent name 5. order_time 6. rain_mode 7. on_time 

95 unique orders are placed according to this dataset.

There are 3 modes namely -Heavy,moderate,drizzle with 0,2 and 5 as it's respective identifiers from the dataset.

There are 49 unique restaurents name present in the order history in the given dataset.

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.

From the above result, 2021, October holds the highest number of Orders.

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.