Feita no Excel e SQL
- Análise com o objetivo de saber os sabores, tamanhos e dias que mais vendem.
- Aumentar o faturamento e conseguir vender em dias de baixa procura.
- O dataset contém as seguintes informações:
- 11 colunas e 49.621 linhas
- Fiz algumas queries no SQL para obter informações relevantes e precisas, depois utilizei o Excel para a criação de KPIs e dashboard.
- Visão geral das queries
- select SUM(total_price) AS Total_Revenue FROM pizza_sales
- select SUM(total_price) / COUNT(distinct order_id) as Avg_Order_Value from pizza_sales
- select SUM(quantity) as Total_pizza_sold from pizza_sales
- select COUNT(DISTINCT order_id) as Total_Orders from pizza_sales
- select cast(CAST(sum(quantity) as decimal(10,2)) / CAST(count(distinct order_id) as decimal(10,2)) as decimal(10,2)) AS Avg_Pizza_Per_Order from pizza_sales
- select DATENAME(DW, order_date) as order_day, COUNT(distinct order_id) as total_orders from pizza_sales group by datename(DW, order_date)
- select DATEPART(hour, order_time) as order_hours, COUNT(distinct order_id) as Total_Orders from pizza_sales group by DATEPART(hour, order_time) order by datepart(hour, order_time)
- select pizza_category, cast(sum(total_price) AS DECIMAL(10,2)) as Total_Sales, CAST(sum(total_price) * 100 / (select sum(total_price) from pizza_sales) AS decimal(10,2)) as PCT from pizza_sales group by pizza_category
- select pizza_size, CAST(SUM(total_price) AS DECIMAL(10,2)) as Total_Sales, CAST(SUM(total_price) * 100 / (SELECT SUM(total_price) from pizza_sales) AS DECIMAL(10,2)) AS PCT from pizza_sales group by pizza_size order by pizza_size
- select pizza_category, SUM(quantity) as Total_Quantity_Sold from pizza_sales where MONTH(order_date) = 2 group by pizza_category order by Total_Quantity_Sold DESC
- select top 5 pizza_name, SUM(quantity) as Total_Pizza_Sold from pizza_sales group by pizza_name order by Total_Pizza_Sold DESC
-select top 5 pizza_name, Sum(quantity) as Total_Pizza_Sold from pizza_sales group by pizza_name order by Total_Pizza_Sold ASC
No Excel eu criei as KPI's e tabelas dinâmicas para maior fluidez na vizualição
E assim ficou o dashboard!