CDW110v Caboodle Data Model Fundamentals exam 2023 with 100% correct answers

CDW110v Caboodle Data Model Fundamentals 2023 Caboodle Dictionary - ANSWER-Basic metadata for tables. Find Descriptions of tables and columns available in data model. Identify tables that can be linked together. Caboodle Dictionary Editor - ANSWER-In depth view of Caboodle ETL packages and data lineage. Shows Clarity tables data that extracted from when populating tables, which ETL packages are used by Caboodle tables and dependencies amongst the tables in Caboodle. Caboodle Executions - ANSWER-Where Caboodle administrators can create, edit, run and monitor executions. Can be used to schedule recurring executions. Caboodle Workqueues - ANSWER-Logs the different types of issues that can occur during the ETL process that require manual intervention to resolve. Caboodle configurations - ANSWER-modify settings, perform customizations such as adding attributes to the data model and view reports related to Caboodle configuration and operation. Caboodle BI Developers - ANSWER-write Caboodle reports and should have access to the Caboodle Dictionary on the Console. Dictionary provides table descriptions, data lineage for tables and columns and foreign key information. BI Developers should be familiar with Caboodles dimensional data model and at least one area of healthcare reportings such as revenue or clinical reporting. Caboodle Administrators - ANSWER-have access to all activities on the Caboodle Console. Administrators monitor executions, troubleshoot work queue errors and establish system level configurations. Caboodle ETL Developers - ANSWER-create custom EPIC and n on Epic content for extraction into the data warehouse, document their work in the dictionary editor and test their work using the ETL tools available in the console. Custom development notes and documentation relevant to report writers will be visible in the dictionary. Why use Caboodle - ANSWER-Accessibility, Efficiency and fewer tables and simpler joins. SSIS package - ANSWER-SQL Server Integration packages : Data is extracted from source systems (Clarity) transformed in the staging database and presented for users in the reporting database. DMCs - ANSWER-Data Model Components Data Model Compenents - ANSWER-collection of metadata tables that support the ETL process and reporting views stored in the FullAccess schema. DMC type and suffixes - ANSWER-Each DMC gets a type and suffix. Dim for dimensions, Fact for facts, Bridge for bridges, Datamart for data marts, AttributeValueDim for EAV tables, X for custom tables Caboodle Star Schema - ANSWER-where one central fact table will join to many associated lookup or dimension tables. Dimensional Data Model - ANSWER-This structure intentionally makes some compromises to the normalized data model used by Clarity in order to facilitate report writing. The trade off is that it requires more complicated ETL process to maintain. Caboodle consists of a reporting database and a staging database - ANSWER- dbo - ANSWER-Staging database: import tables and mapping tables live here. Used by administrators for moving data into Caboodle. Reporting Database: dbo schema stores reporting data and acts as the data source for SlicerDicer. Caboodle Dictionary reflects the contents of the dbo schema EPIC - ANSWER-Staging Database: Epic schema on the staging database contains the _IdLookup tables, which map source IDs to system-generated Caboodle primary keys in the reporting database. Reporting Database: Prior to Epic 2018 this schema stored the tables used by the SlicerDicer patients data model. FullAccess - ANSWER-Staging Database: The FullAccess schema does not exist on the staging database Reporting Database: The FullAccess schema houses view that timplify reporting. FullAccess should be your default schema when reporting.