In my opinion, one of the main advantages of TimeXtender is that, when used correctly, it encourages you to focus on designing a solid semantic model rather than getting bogged down in code optimization. Incremental loading becomes a straightforward process, accomplished with just a few clicks, rather than having to build it from the ground up or risk inconsistent methods among different developers.
As you become more familiar with how TimeXtender works, you may find that you can replace or simplify views by using lookups and adopting a table-to-table approach. If you notice that you’re repeatedly applying the same transformations or building views in a similar way, it’s a good idea to turn that process into a snippet.
Finally, if you’re dealing with multiple data connections that share the same configuration, you can streamline your workflow by adding an additional source to your main source. This allows you to manage transformations or changes across all sources at once, reducing the effort required to update each one individually. Review collected by and hosted on G2.com.
As an organization currently managing over 300 data sources across two production environments, we are increasingly feeling the pressure to stay ahead of any changes in our data. Over time, we anticipate reaching a point where we must choose between finding a way to maintain fast data loads that continue to meet our customers' expectations, or considering moving away from bundling the data altogether and looking into alternative products. Review collected by and hosted on G2.com.
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