We currently support data import through API queries, but while this gives a finer control over the data that’s being sent, you would also need to format the data and schedule queries.
We wanted to make all of this process much faster to people willing to give us straight (read only) access to their database both by handling the daily tasks on our side and by sticking to SQL row formatting and deport all the pivot work on our side.
Here’s in three steps how you will be able to easily consume our product with an SQL database (following renders are still in development and may not be considered final):
1 – Define your KPIs
For every indicator you want to measure, just provide us with basic information like its unit, its direction and how to aggregate breakdowns (e.g. total sales would be a sum of all the sales while average sales by customer would be an average). The ID is the import part that will allow us to link the data you’ll send further on to the definition of your indicator
You’d typically want to contain your indicators and make them as significant as possible so that the user won’t be lost in a mass of information.
2 – Querying your database
Type in your connection details and test it to make sure the connection works. Then you can just create as many queries as you’d like in plain SQL.
All you need is to name your columns as instructed, we’ll take care of the grouping and aggregation for you 🙂
Above is a working example that will result result in an indicator of sales broke down by customer name.