Working with multiple dates within your data tables in Power BI is quite common, and many new Power BI users get confused with this. Not long ago, I posted an article here similar to this, but I think it’s a good idea to elaborate and give more examples.
Recently, I have noticed that there was a lot of content talking about gzip decompress with Power Query, but I haven't seen someone talking about decompressing .zip files. The truth is that gzip is a most common file extension for data with the Azure suite. We can handle gzip with Azure Data Lake and Azure Data Factory. Anyway, in this article we will check how to decompress a ZIP file to explore your files inside, like a Windows folder in Power Query, in a very similar way as the gzip is done. If you haven't seen how gzip works, you can check this post about it.
Let us take up a scenario where we have customers associated with a store. The store generates a monthly reporting on what their total sales are, and on the report, the total sales metric is summarised at a customer level. Just imagine a table displaying all these customers with the total sales they generated for the store every month. Over time, the number of rows in the table will keep on increasing.
The above scenario can create performance issues in Power BI when working with Big Data or where we have nearly million customers worth of data to display. From a user point of view, this can be quite challenging where users must wait to get the whole table loaded at the first instance.
But, what if there was a way, we can default the table to display only certain number of rows and then let the user control how many rows they want to see in the table visual?