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CDW 110 LATEST 2023 WITH SATISFIED SOLUTIONS

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CDW 110 LATEST 2023 WITH SATISFIED SOLUTIONS CHAPTER 1-Caboodle Console - The Caboodle Console is a webapplicationhousedon the Caboodle server. It includes the following: Dictionary Dictionary EditorExecutions Work Queue Configuration -Data Warehouse - In a data warehouse, multiple source...

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  • August 31, 2023
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  • 2023/2024
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CDW 110 LATEST 2023 WITH SATISFIED SOLUTIONS CHAPTER 1-Caboodle Console - The Caboodle Console is a web application housed on the Caboodle server. It includes the following: Dictionary Dictionary Editor Executions Work Queue Configuration -Data Warehouse - In a data warehouse, multiple sources may load data pertaining to a single entity. This means that more than one package may populate a given row in a Caboodle table. As a result, there may be multiple business key values associated with a single entity in a Caboodle table. -ETL - Extract, Transform, Load -SSIS Package - The architecture of Caboodle includes a staging database and a reporting database. Data is extracted from source systems (like Clarity), transformed in the staging database, and presented for users in the reporting database. This movement of data is realized via a set of SQL Server Integration Services (SSIS) packages. -Data Lineage - Generally, data lineage refers to the process of identifying the source of a specific piece of information. In Caboodle, data lineage is defined at the package level. -Star Schema - The standard schema for a dime nsional data model. The name refers to the image of a fact table surrounded by many linked dimension tables, which loosely resembles a star. The Caboodle data model structure is based on a "star schema" ‐ where one central fact table will join to many associated lookup or dimension tables. This structure provides the foundation of the Caboodle data model. -DMC - DATA MODEL COMPONENT No table in Caboodle "stands alone." Each is considered part of a Data Model Component, which refers to the collection of metadata tables that support the ETL process and reporting views stored in the FullAccess schema. Each DMC gets a type. Strict table naming conventions are followed in Caboodle, so that a table's suffix provides information about its structure and purpose. These suffixes are: · Dim for dimensions (e.g. PatientDim) · Fact for facts (e.g. EncounterFact) · Bridge for bridges (e.g. DiagnosisBridge) · DataMart for data marts (e.g. HospitalReadmissionDataMart) · AttributeValueDim for EAV tables (e.g. PatientAttributeValueDim) · X for custom tables (e.g. CustomFactX) -Staging Database - The Caboodle database into which records are loaded by SSIS packages and stored procedures. -Reporting Database - The architecture of Caboodle includes a staging database and a reporting database. Data is extracted from source systems (like Clarity), transformed in the staging database, and presented for users in the reporti ng database. This movement of data is realized via a set of SQL Server Integration Services (SSIS) packages. -Dbo Schema - STAGING DATABASE Import tables and Mapping tables live here. This is primarily used by administrators for moving data into Caboodle. REPORTING DATABASE The dbo schema stores reporting data and acts as the data source for SlicerDicer. The Caboodle Dictionary reflects the contents of the dbo schema. -FullAccess Schema - STAGING DATABASE The FullAccess schema does not exist on the Staging database. REPORTING DATABASE The FullAccess schema houses views that simplify reporting. FullAccess should be your default schema when reporting. -Identify key characteristics of the dimensional data model - MADE for report writers. · Simpler and more intuitive. · Easily extensible. · More performant.. -Identify the benefits of the dimensional data model? - It centralizes its structure around more flexible fact and dimension tables, and the joins between these are more intuitive. -Identify documentation resources for reporting out of Caboodle - Caboodle Dictionary Reporting with Caboodle document Caboodle ER diagram

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