Data for the tutorial can be obtained by downloading CSV files from: https://www.census.gov/popest/data/intercensal/state/ST-EST00INT-02.html For the tutorial I downloaded data for Alabama, Alaska and Arizona into a folder. Open the CSV files, and notice that all of them have the same layout. In this tutorial we are going to: Read data from the folder data source
This tutorial shows how to create a Star Schema using Power BI Desktop. Data for the tutorial can be obtained by downloading Excel file from here Very often our analysis starts with a flat data set that contains all of the pertinent columns in a single table that looks like the one above. As we
It’s common that data is laid out across columns in Excel for reporting purposes. E.g. Revenue for each product is laid out across the columns in excel for each month. However this may not work well as a data source. Power Query provides Unpivot option to solve this issue. Sample workbook can be downloaded here.
While migrating a power query solution across environments (Dev to UAT to Prod) changing connection variables for each power query is a tedious task. Here is a way to make the connection variable dynamic. The sample here has two power queries connecting to SQL server source. Create an excel table and call it Parameter with
Power Query has a feature that can be used to drill into details. This is particularly useful when working with 32 bit excel. Sample workbook can be downloaded here. Here are the steps. For the purposes on the tutorial let’s load Sales data from an excel table (this could be from a database). Highlight Sales
Data for the tutorial can be obtained by downloading the following files: Exchange Rate File Working with Currency File Step 1: Load Sales Data to Data Model Open workingwithcurrency.xlsx, highlight Sales Data table, pick PowerPivot from the ribbon and select Add to Data Model Step 2: Using Power Query to transform Exchange Rate data