Overview: Data Types

Note: For all integrations built by Databox, the current Data Types have already been set. Setting Data Types is relevant only for pushing custom data via the Databox API and all SQL integrations.

Databox has powerful data modeling functionality built-in. This means, it’s not just a visualizing tool for mirroring exact numbers pushed in, but it will also allow you to apply various data aggregations, such as sum, average, min, max, count and average, so that your data will be visualized correctly. (Read more about Data Aggregations.)

What are Data Types?

Data Types are descriptors that give context to the data and define what kind of numbers you are pushing in. You can push different types of data: from unprocessed raw numbers to current balances, averages, uniques, rates and more. Each metric can have a different Data Type.

To handle this wide range of data, your input has to be described so that Databox can enable the correct data modeling to be run on it.

By default, we assume that you’re sending the difference from previous (‘Diff’). This is the right type when pushing event value. The best example is to push the deal/sale size every time a deal/sale happens. To see the total of sales in a day or longer date range, we will sum those sales pushed on a specific day or period of days.

However, if your data does not conform to these rules, don’t worry, we support other Data Types too.

In the case of pushing clicks on a specific button on the website, you would need to push new clicks only (one push for each click or batched together every hour or so) to use the default data type. If you would like to push the total value of clicks (increasing over the day and then starting over at 0 after midnight), you would need to set the sum for day Data Type. In that case, we would show the latest value for a specific date to be the real and final value, and sum those latest daily values when showing the total for a longer period of days.

These are just two examples, please check the Data Types list below.

Basic list of supported Data Types

Difference from previous *Default

Raw unprocessed data (event data) that allows all aggregations. Each sent value represents an increase or decrease in value. For example, if you trigger an update to Databox on every transaction made in your online store and send us the value, we’ll sum these values up to show the total amount of income.

Example: Deal value pushed each time a sale happens.

Difference of average from previous

Raw unprocessed data similar to the ‘difference from previous’ Data Type, but for the  case you would like to display average values. Both aggregation functions will be set to Average (AVG) by default.

Example: Average order value

Sum for day

Default  type for fully aggregatable data ( non -uniques). If you push values many times a day, the latest value counts as the ‘real and final’ value for that particular day. The value is reset to 0 at midnight UTC. Most cloud services treat data this way.

Example: Current number of all visitors this day (increasing with each push)   

Minimum for day

Similar to Data Type as for ‘Sum for  day ’, but the aggregation functions will be set to minimum (MIN) by default, to display the lowest pushed value in a given period of dates.

Maximum for day

Identical data as for ‘Sum for  day ’, but the aggregation functions will be set to maxim (MAX) by default, to display the highest pushed value in a given period of dates. 

Example: Highest closed deal

Unique Daily value

Pushing latest value for today, with data that has been irreversibly processed before and where further data aggregation is not allowed. 

Example: Unique users this day, percentage or average values for this day. (With this Data Type, daily numbers can not be further calculated to determine values for longer time periods.)

Overall value

Overall  current value for metrics, where data doesn’t ever  reset  but represents the current status. The latest value pushed is the only one that matters. (Metrics with this Data Type should be visualized with   an ‘  All time’ date range.)

Example: Facebook likes, Current account balance

Unique Daily Value for individual Date Ranges

Pushing latest value for a specific date range, with data that has been irreversibly processed before and where further data aggregation is not allowed. This is practical with using metric mappings, where a specific date range is mapped to another unique metric.

Example: Unique users for last 7 days (by using type ‘Unique7dDailyLatest’).

How to set the Data Type for a specific metric?

The Data Type can be set after the first value for a metric has been pushed to Databox. Metrics are bundled in Data Sources (tokens) and are accessible from the Databox web application ( https://app.databox.com) under the Data manager tab. Custom metrics can be pushed to the default access token (‘Token’) or a new token created by the user. To see the metrics pushed to a token and set their Data Types, click on the context menu for that token and then ‘Edit metric keys’.

This page allows you to change the display name of the metric, the Data Type, default number format, compare number format, compare function, inverted value option (optional, if checked increases will be marked with red and decreases with green, meaning lower values are better) and available date ranges (optional, if you want to disable some date ranges from being selected when setting up Databoards).

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