Data Forecasting module forecasts your data into the future and helps you to better understand where your business is heading. This is extremely useful to monitor:
- Website Visitors
- Users Actions (purchases)
- Quantities of transactions
Any kind of data that is important to your business can be forecasted to give you the peace of mind that you will be the first to know.
Don’t have the time to read the whole article? Check out this 2 min video:
Step 1 – Select a Table
Start by choosing the table or view that has the data that you would like to forecast. In our case bellow we are going to do some forecasting on a table that has FX rates. We want to forecast EUR to USD Exchange rates.
Step 2 – Select Date column
A date column is the one that defines the timely flow of your data. Usually it is the timestamp of when the records was created, such as created_at field.
Step 3 – Select Value column
Next up is to choose the actual data that you would like to be forecasted. Here you can choose to count, average or sum the values before the forecasting algorithm is executed. Here we would like to forecast the average fx rate (column rate).
Step 4 – Add filters (optional)
Here you can choose to filter your data to run forecast only on the subset of your data, such as a particular product or service. Use the Query Preview window to see exactly the query we will run to fetch the data for forecast.
Step 5 – Choose the lookback interval
The parameters forecast days and lookback interval can be left as they are. However, if you would like to adjust them here is a description of each one:
Forecast days – how far into the future would you like to forecast the data?
Lookback interval – determines how far back the data is gathered for the model. Smaller lookback period will build a forecast model that will be reflective of the recent trends, while a larger lookback window will build a forecast that will be based on longer-term trend.
Once you are satisfied with your model, click Run to test it and save it.