Adding or updating numbers
For external usage, 4Straction numbers are divided into 4 different time periods:
And all numbers have the following dimensions:
And all numbers can be stored in multiple levels including
- company top level
- by products
- by market players (such as customers, competitors..)
- by geographical areas
- by legal units
- by teams
Please study how this works in the service main interface before importing data.
For simple usage, there is a call in all time options: mergeTargetValue(). All merge target values take:
- required time parameters (such as year and month)
- indicator identifier
- CorporateStructureLink (that defines what "level" you are using")
- actual, budget, forecast and goal
- value source (internal information to show users from what source information has arrived). Optional
- comment (Additional comment for the data. Visible in dashboards)
Zeroes and empty data
Currently used OpenAPI spesification cannot seperate between a NULL and a zero. This is why we have added few methods to help with that. Instead of mergeTargetValue, you can also call mergeTargetActualValue, mergeTargetBudgetValue.. and so forth. This will ignore other values if you don't want to touch them.
How to work with changing data
When you work with remote data storages, there might be instances that the data you imported has changed for some periods, so what you need is to update the data to all time periods that you have worked with. In this case you have 3 options:
*Keep track of all data from remote system'
Keep track of sent information and send only changes. This is time consuming and in some cases would required middle-system to keep track of this data, if you are directly working with 3rd party systems you don't have access to.
Send all time periods
When you synchronize information, you can always send all time periods from a given periods such as from year 2005 to 2018 and send updates of empty months and non-empty months.
Clear information before udpating
In some cases it would be useful to just clear all indicator data before importing it. See next section for more details.
Clear indicator values
When you start working with data, you might come up with bad data due to tests or corrupted data from upstream system. Then it is useful to just clear all information from an indicator before using it. You can call the following API resource for this.
Remember to clear just that dimension that you want, since users might work with budget or goal values in the main application even if you work with actual values in the API.