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Then, within the query editor, we’re going to optimize the table or make it as a single table. That’s why we need to create this intermediary step called staging area for these tables. Moreover, we shouldn’t leave them with the same look and shape like their initial query. Hence, we have to find a way to integrate them while still maintaining those queries, so they’d still continue to find the data. We need to query this data so we can bring it into our model. If we check out the Sales Orders tables in this demo data, we’ll notice that it is exactly the same data that only differ in a year. Let’s see how our demo data might look from disparate data sources that we may have to connect in the future.
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Here, we have tables like Channel Details, Customers, Products, Regions, and a range of Sales tables for 2014, 2015, and 2016. Staging queries via Power Query editor is an intermediary step to achieve this. Therefore, we need to utilize the queries to integrate our tables or data into a more refined and optimized model. If we look at our model right now, we already have the essential elements, but it’s still too complicated. This is a recommended data access method. Staging queries can be used to configure and expose the data sources parameters to the dimension and fact table queries of the dataset.įor Power BI datasets, we need to define parameters specific to the data sources, and develop a staging query which references those parameters.