After Call Work
Also known as ACW. The state where a device, on behalf of an agent, is no longer involved with an Automatic Call Distributor (ACD) call. While in this state, the agent is performing administrative duties for a previous call (or another media interaction) and cannot receive further calls from the ACD.
See also Ready and Not Ready.
Reporting And Analytics Aggregates
Also known as RAA. An optional Genesys Info Mart process that creates and populates predefined aggregation tables and views within an Info Mart database. RAA aggregation tables and views provide the metrics that summarize contact center activity to facilitate reporting, and serve as the primary source of data for the GI2 and Genesys CX Insights reports. RAA is required for GI2 and Genesys CX Insights environments.
Genesys Interactive Insights
Also known as GI2. A presentation layer that extracts data from the Genesys Info Mart database, and presents it in readable reports to enable business and contact center managers to make better business decisions for streamlining operations, reducing costs, and providing better services.
For Genesys Cloud customers, depending on the release of Genesys Cloud that you are using, historical reporting is available through either the Genesys Interactive Insights (GI2) interface, or through Genesys CX Insights.
Extract, Transform, And Load
Also known as ETL. The ETL processes extract data from various data sources; transform the data into a format and structure that is suitable for subsequent business purposes; and load the data into a target data store (other database, data mart, or data warehouse).
Populating Genesys Info Mart Data
Bringing Data into Info Mart
Extract, transform, and load (ETL) is performed by two main jobs: Job_ExtractICON and Job_TransformGIM. Deployments in which Genesys Interactive Insights (GI2) or Reporting and Analytics Aggregates (RAA) is installed also use Job_AggregateGIM.
- Job_ExtractICON extracts new and changed data from IDBs and stores the data in the GIDB tables, as discussed in Populating Low-Level Details.
- Job_TransformGIM transforms the data from GIDB into the dimensional-model (fact and dimension) tables.
- Job_AggregateGIM calculates or recalculates metrics and stores them in the aggregate tables in the Info Mart database, based on the data that was added or changed during the last transformation run.
Genesys Info Mart extracts multimedia interaction data while the interactions are still active, and multimedia interaction records might be updated frequently and over large time intervals. Similarly, although Genesys Info Mart extracts voice interactions only after they have completed, After Call Work (ACW) might cause end timestamps in Info Mart records for call-related activity to be updated in a subsequent ETL cycle. Therefore, the timing of your reporting queries can affect reporting results.
When generating and interpreting reports, remember to allow for data updates that might occur over multiple ETL cycles because of continuing activity during long-lived multimedia interactions or because of ACW after voice or multimedia interactions end. For example, for voice interactions, allow for the maximum amount of time that can be spent on wrap-up activities, as well as for the ETL schedule and ETL execution time. You might need to regenerate reports to guarantee final results.
Populating Low-Level Details
The Global Interaction Database (GIDB) is an area within the Genesys Info Mart database schema in which the low-level interaction data from any number of IDBs is consolidated for further processing.
Genesys Info Mart Server uses the low-level details data from GIDB tables to produce data that is suitable for end-user reports and to populate the fact and dimension tables that compose the Info Mart dimensional model.
Some configuration-related GIDB tables (see Info Mart GIDB Tables) are included in your data export to support data in the exported fact tables.
The DATE_TIME Dimension
The DATE_TIME dimension enables facts to be described by attributes of calendar date and 15-minute time interval. All interaction-related fact tables use only the DATE_TIME time dimension. No other time-dimension fields are used.
For more detailed discussion of the DATE_TIME dimension, see Representing Dates and Times of Day.
Populating Specific Types of Data
See the following pages for detailed discussion about: