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New managed Incremental Extract Pattern
[et_pb_section admin_label=”section”][et_pb_row admin_label=”row”][et_pb_column type=”4_4″][et_pb_text admin_label=”Text” background_layout=”light” text_orientation=”left” text_font_size=”14″ use_border_color=”off” border_color=”#ffffff” border_style=”solid”] Dimodelo Data Warehouse Studio now allows you to extract only changed data from your source system, reducing load on your source systems and overall ETL duration. I.e. To do change data capture (CDC) at the source. Dimodelo Data Warehouse Studio now includes a managed…
Conversations with Data Warehouse Experts – James Serra
In this episode, it is my pleasure to speak with James Serra, Data Platform Solution Architect and Data Warehouse Evangelist at Microsoft. He is a thought leader in data warehousing and data management with over 25 years of experience in data modeling, data governance, and development methodologies. James is also a popular and prolific blogger…
Tutorial 1 – Deploy
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A Dimodelo Data Warehouse Automation Case Study Podcast
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Join me for an enlightening conversation with Dr. Barry Devlin, regarded as one of the world’s leading authorities on business insight and data warehousing. He was responsible for the definition of IBM’s data warehouse architecture in the mid-1980s which in our view makes him the “Godfather” of the data warehouse . He is now founder…
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.