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Imagauthamam
Helper I
Helper I

Time Series Forecasting Dataset in Power BI

I'm trying to do time series forecasting in Power BI. 

Before I start doing it, I have some doubts in how we can Prepare source dataset.

Just want to understand the structure of data.

Let's say I have a department and in each department there are multiple Teams, I want to time series forecasting on Total Sales By each department.

I can prepare the data in the below options:

 

Screenshot 2023-06-08 012040.jpg

 

Most of the tutorials which I have seen online is using Option 2. But I prefer Option 1

Because in future if there are more new departments coming 1, then it can be added at the row level, whereas in Option-2 I need to add more and more columns each time.

 

My Question is :

1. Can I use the structure in Option-1 for preparing my dataset?

2. If Yes, in the Date column, I can see 1st June has 3 records for each team in a department. So is there any condition whether a row should have a date only once? 

3. In Option-1, Let's say I want to predict total sales By department. Will adding a addition column like Team Name have any impact while preparing models for time series forecasting?

I would be really glad if someone could help. Thanks in advance.

1 ACCEPTED SOLUTION
lbendlin
Super User
Super User

1. Option1 is by far the better option.

2. Add an index column if you are concerned about disambiguation

3. no, in fact it will help tune the predictor engine.

View solution in original post

1 REPLY 1
lbendlin
Super User
Super User

1. Option1 is by far the better option.

2. Add an index column if you are concerned about disambiguation

3. no, in fact it will help tune the predictor engine.

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