As I delved into Schuler’s Data Warehouse course on Udemy, I stumbled upon a concept that left me wondering: why does the transactional date from the source system serve as a good delta value for running the next incremental load? As an analyst new to data engineering, I couldn’t help but question how a datetime value could be an effective delta value.
My initial thought was that using a transactional ID would be a better option. After all, couldn’t two transactions have the same date and timestamp? But as I dug deeper, I realized that there’s more to it than meets the eye.
## The Power of Transactional Date
The transactional date serves as a natural delta value because it indicates when a specific transaction took place. This date can be used to identify new or updated records in the source system, making it an ideal candidate for incremental loads.
## Why Transactional ID Isn’t Enough
While a transactional ID might seem like a more unique identifier, it doesn’t provide the same level of context as a transactional date. The date gives you a timeline of when changes occurred, allowing you to load only the necessary data.
## Incremental Load Benefits
Using a transactional date as a delta value enables efficient incremental loads. This approach reduces the amount of data being loaded, making the process faster and more efficient.
## Conclusion
In conclusion, the transactional date serves as a good delta value because it provides a natural way to identify new or updated records in the source system. By leveraging this date, you can ensure efficient incremental loads and keep your data up-to-date.
*Further reading: [Data Warehouse Incremental Load Strategies](https://www.datavail.com/blog/data-warehouse-incremental-load-strategies/)*