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In our ongoing Data Vault Friday series, our CEO Michael Olschimke tackles a compelling question from our audience.
“From one of our source systems, we receive customer information in real-time messages. These messages are set up in a way that they always contain the business key(s) to identify the customer and the attribute(s) that have been entered, changed, or set to null.
For example, the first message includes customer creation with various attributes, including an email address and, of course, a Business Key. A second message later might include the Business Key, a new email address, and a new attribute (e.g., birthplace) that did not exist in the previous one.
We have a list of attributes that the end user is interested in, in our Information Mart, specifically in the Customer dimension. How would you manage this in the Data Vault architecture?”
In this enlightening video, Michael begins by discussing the design often encountered in such scenarios, highlighting areas for potential improvement. He then shares his insights on how to efficiently manage the message stream within the Data Vault 2.0 model. The discussion touches on optimizing the design for better usability in the Information Mart while maintaining the integrity and efficiency of the Data Vault architecture.
Meet the Speaker
Julian Brunner
Julian Brunner is working as a Senior Consultant at Scalefree and studied Business Informatics and Business Administration. His main focus is on Business Intelligence, Data Warehousing and Data Vault 2.0. As a certified Data Vault 2.0 Practitioner he has 5 years of experience with Business Intelligence solutions and Data Warehouse development with the Data Vault 2.0 standards. He has successfully consulted customers from the banking and consulting sector.
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