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In our continuous series, our CEO Michael Olschimke delves into a thought-provoking inquiry posed by a member of our audience:

“Why do numerous illustrations of Point-In-Time (PIT) tables utilize load datetimes instead of applied datetimes from the source, despite the fact that analysts generally aim to restore data for a specific datetime as it existed in the source? Are there instances of PIT table implementations that incorporate both applied datetimes and load datetimes?”

Michael delves into the intricacies of Point-In-Time (PIT) tables, exploring the rationale behind the prevalent use of load datetimes versus applied datetimes in these structures. He addresses the challenges and considerations in designing PIT tables that accurately reflect the state of data as per the source system, while also considering the need for historical restoration based on specific datetimes. Michael provides insights into potential approaches or hybrid models that combine applied datetimes and load datetimes to meet both analytical requirements and data reconstruction needs effectively within PIT table implementations.

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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