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In our continuous series, CEO Michael Olschimke addresses a question from the audience:

“What are the options to virtualize the load end date in Data Vault? We work on an embedded solution and the Window function (LEAD/LAG) is not fast enough.”

The viewer raises a critical concern regarding the virtualization of the load end date in a Data Vault environment, especially in the context of an embedded solution. The challenge lies in the performance limitations of certain window functions like LEAD/LAG, prompting the exploration of alternative options.

Michael delves into potential strategies and solutions for efficiently managing load end dates in Data Vault. The discussion encompasses various approaches to enhance virtualization, ensuring optimal performance without compromising speed or efficiency.

By sharing insights into the intricacies of load end date virtualization, Michael provides valuable guidance for organizations grappling with embedded solutions. The exploration of alternatives offers a nuanced perspective on optimizing this crucial aspect within the Data Vault framework.

Meet the Speaker

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

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