Data types and measures

This guide provides information about the data types and measures used in Adverity.

Data types used in Adverity

Adverity uses a number of data types for your data.

The table below provides information about the data types in Adverity that are universally used in data management.

Data type

Notes

Example

String

Use for dimensions, such as names, titles, and descriptors.

EN_Campaign_21

Long

Use for integer metrics without decimal points.

16

Float

Use for non-integer metrics with digits after a decimal point.

16.523

Date

Use for dates. Adverity recognizes common date formats.

(Recommended) Use the ISO 8601 format YYYY-MM-DD.

2021-03-11

DateTime

Use for date and time. Adverity recognizes common datetime formats.

(Recommended) Use the ISO 8601 format YYYY-MM-DDThh:mm:ss.

2021-03-11T16:23:41

Boolean

Use for binary metrics. The values are either 0 (false) or 1 (true).

0 or 1

The table below provides information about the data types that are specific to Adverity.

Data type

Notes

Example

Percentage

Use for rates and percentages. Adverity automatically multiplies the values by 100. For example, 0.1 is displayed as 10%.

0.1

Currency

Use for metrics that express values in a currency.

10

JSON

Use for layered metrics with JSON-compatible formatting.

{"firstName": "Jane", "lastName": "Doe"}

Formula

Use to send information about formulas to the Google Sheets destination.

=A1 + B1

Duration

Use for metrics that express a time duration.

(Recommended) Use the ISO 8601 format PnYnMnDTnHnMnS.

P2DT3H

Data type estimation in Adverity

When you fetch data, Adverity automatically assigns a data type to each source field column in your data extract. When you configure Data Mapping for a column, you can choose a different data type for the target field assigned to this source field. The data type of the target field will be used when loading data into your destinations. For more information about configuring Data Mapping, see Applying Data Mapping to a datastream.

Limitations

The Currency data type cannot be assigned based on estimation. This data type must be assigned to a field by configuring Data Mapping for the field or manually changing the source field type.

Data type weight hierarchy

Adverity uses data type weights to select the best estimated type. The diagram below shows the data type weight hierarchy used during estimation, where String has the lowest weight and Boolean the highest. Data types on the same horizontal level have equal weights.

The default estimated data type is String.

Estimating data types in Adverity

To estimate the data type for a column, Adverity uses the following steps:

  1. Adverity determines all data types to which all values in the column can be converted.

  2. Out of the possible data types, Adverity selects the type with the highest weight. This way the estimated type matches the column's data the most closely.

  3. If the estimated data type is Date, Adverity checks the format. If the date format contains "%H", then the DateTime data type is assigned.

Examples of data type estimation

Example 1

The source column contains JSON values.

The column's values can be correctly converted to two data types: JSON and String. The JSON data type has higher weight than String. So Adverity estimates the column's data type as JSON.

Example 2

The source column contains integer values.

The column's values can be correctly converted to three data types: Long, Float and String. Out of these data types, Long has the highest weight. So Adverity estimates the column's data type as Long.

Measures used for metrics in Adverity

The table below provides information about measure types, the mathematical function underlying the values in a metric field.

Measure type

Notes

Sum

Use for metrics that display the sum of values. Applicable for most metrics with values that can be summed up across several data sets, such as clicks, impressions.

Average

Use for metrics that display the average of values by dividing the sum of values by the number of data sets.

Count

Use for metrics that display the number of data sets.

Min

Use for metrics that display the minimum value across all data sets.

Max

Use for metrics that display the maximum value across all data sets.

None (Metric)

Use for metrics that do not have an underlying mathematical function, such as campaign reach.

None (Dimension)

If you load data into Adverity Data Storage, Adverity treats the data type of a field that you set up with this measure as a String regardless of the data type you select in the Type field.