Attribution

This function is used to perform click stream analysis.It has many kinds of computation models and distribution models.

Options

EventColumn: Specifies the name of the input column that contains the clickstream events.
Output Schema: Output Schema, if Volatile is true then use user login as the schema.
Output Table: Output Table
VAL Location: VAL Location
Volatile: Specifies whether the table should be a VOLATILE table. If true, then the table is automatically deleted, otherwise it is users responsibility to remove or clean it up for space.
TimeColumn: Specifies the name of the input column that contains the timestamps of the clickstream events.
WindowSize: Specifies how to determine the maximum window size for the attribution calculation: rows:K: Consider the maximum number of events to be attributed, excluding events of types specified in excluding_event_table, which means assigning attributions to at most K effective events before the current impact event.seconds:K: Consider the maximum time difference between the current impact event and the earliest effective event to be attributed. rows:K&seconds:K2: Consider both constraints and comply with the stricter one.

: Connection to a Teradata Database Instance
: Contains the click stream data, which the function uses to compute attributions.
: Contains the click stream data, which the function uses to compute attributions.
: Contains the click stream data, which the function uses to compute attributions.
: Contains the click stream data, which the function uses to compute attributions.
: Contains the click stream data, which the function uses to compute attributions.
: Contains one varchar column (conversion_events) containing conversion event values.
: Contains one varchar column (excluding_events) containing excluding cause event values.
: Contains one varchar column (optional_events) containing optional cause event values.
: Defines the type and specification of the first model. For example: Model1 ('EVENT_REGULAR', 'email:0.19:LAST_CLICK:NA', 'impression:0.81:WEIGHTED:0.4,0.3,0.2,0.1')
: Defines the type and distributions of the second model. For example: Model2 ('EVENT_OPTIONAL', 'OrganicSearch:0.5:UNIFORM:NA', 'Direct:0.3:UNIFORM:NA', 'Referral:0.2:UNIFORM:NA')