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Creating and Using a Derived Staging Table
What is a derived staging table? It’s a table created in your Staging database that derives its data from other already existing Staging tables. Its useful for creating aggregations, or allocations of data prior to the transform and load process into your Data Warehouse. It can also be useful for tables that don’t have any…
Dimodelo Data Warehouse Studio 2.15 – Whats New
Dimodelo Solutions is proud to announce the release of version 2.15 of Dimodelo Data Warehouse Studio, its data warehouse automation tool for the Microsoft data platform. In this release we have added support for the Microsoft APS platform and SQL Server 2017. We have also redesigned our data management architecture from the ground up, introducing…
Tutorial 1 – Run ETL Batch
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Defining a Dimension with Smart Keys
While conventional wisdom (and Kimball) says that using meaningful identifiers for surrogate keys is a bad idea, there are some exceptions where it makes sense. Typical examples include: Calendar. An example of a Calendar smart key is – year, month, day e.g. 20110721. A DateTime value can be converted to this date format using this statement convert(char(8),date, 112)….
The Dimodelo Data Warehouse Studio code generation process
This post discusses in detail how Dimodelo Data Warehouse Studio generates code to create and manage a Data Warehouse, including creating and managing Data Warehouse Databases, Tables and ETL procedures. While Dimodelo Data Warehouse Studio has a set of predefined Generation Templates and Generation Providers , it is also extensible, allowing end users to create their own Generation Templates and Generation Providers.
Tutorial 1 – Getting Started
In this tutorial you will learn how to use Dimodelo Data Warehouse Studio to:
Create a new Data Warehouse project.
Create a connection to a Source System.
Use the Wizard to generate the Meta Data for a Data Warehouse and its Extract, Transform and Load processes (ETL).
Generate the code to create the Data Warehouse and Staging databases, and the ETL to move data from the source through to the Data Warehouse.
Deploy the code to the Server.
Execute the ETL batch.