In short, how do i calculate yearly unit production cost based on fixed cost divided by amount produced?
I am making dashboard in power BI for a video production studio company. They have a fixed cost per month and year based on the salary of the employees, production equipment etc. Lets say that the monthly fixed cost is $20 000. As tables show below i have a column called videos recorded, which i need to tie to the month, and then divided on the fixed cost which will be cost per video on a given month and in summary production cost per video in year 2022. So i want to visualize on a card or table, for July fixed cost were $20.000, we made 30 videos which is $667 per video.
Tables below
Related
As per Microsoft
Estimated charges for the current billing period are updated six times per day.
but it does say how often it calculates the forecast vs actual billing?
Cost & usage data is typically available within 8 ~ 24 hours. And the cost analysis is just a tool to visualize the accumulated data, the interval at which the information are updated might be dependent to several factors as described Here
I am trying to create forecast for next 6 month sales. I am using visual analytics for my forecast.
It is showing me the forecast for Next 6 months.
I don't have employees that are consistent in the data. Like, I am having 28 agents/ employees working in January month and 5 employees working in June month. Here, the employees are not constant in the data. therefore, the above approached method is not the best way for forecast for future months.
How can I make forecast for next n months using measures or columns in Power BI for these types of Inconsistent Hiring and Firing of employees ?
I have a dataset, which is recorded monthly. Another is recorded per 8 day. The problem asks me to forecast the first one with the second one in the model. i.e, the monthly production of apples and overall precipitation per week. How to use precipitation to forecast apple's production?
Another follow-up questions is that if we have a new daily recorded datasets. How to link them together? For example, the monthly production of apples, weekly precipitation and daily temperature.
I'm currently looking at daily sales data of a specific brand over the course of the past year. My objective is to create a formula to roughly estimate the sales growth for future months.
My project isn't going very well, as the brand is very volatile in monthly sales, making it impossible to predict with a basic linear formula. I'm arriving at the conclusion that a single year's worth of sales isn't enough data, and I may have to result to provide a specific formula depending on the month. Is there anything I haven't thought of?
Note: Recording of sales start on the 15th of every month
Your sales are showing seasonality. Consider using sasonal ARIMA models.
The price calculator Azure does not show option for us we inform the number of hours that we use his service. Is the price calculator Windows Azure calculating 24 hours of use per day during the month?
How can I calculate the amount I pay if I access the Windows Azure services for two hours for day throughout the month?
1. The calculator shows both prices per hour and per month. Yet, the monthly price is estimated on average of (fully consumed) 744 hours per month.
2. You're paying for the resources you consume, not for the resources you accessed. That means that even if nobody visited your website/webrole for the entire month, you would still have to pay the compute cost (the bandwidth cost will be $0 though).