Note: If using Office 2016 or later, you may need to open the file in Excel and save it as an Excel 2016 workbook. Download the excel file and save it to a local folder. For the dataset, we will use the General Aviation 2013 Excel file available for public use from. To follow this example, you will need to download Power BI Desktop directly from Microsoft-don’t worry, it’s free-and install it. Now, let’s take a look at Power Query in Power BI Desktop. Once source data is refreshed, all Power BI visualizations are refreshed with the updated data as well. Because Power Query maintains a step-by-step record of every action taken to ingest, transform and load data, you can repeat these same steps when you need to refresh the data. Power BI Desktop and Power Query give users the ability to automate the process of ingesting, transforming and loading data into internal tables in Power BI, which can then be used as a source for Power BI visualizations. What is Power Query? And How Does it Work with Power BI Desktop? However, Microsoft has a tool that can make this process much easier and faster: Power Query in Power BI Desktop. The challenge with this method? The ETL process in Excel is usually a time-consuming, manual process that is not easy to automate. But in some organizations, business users do some of this ETL work right in Excel, often referred to as data shaping and transformation. Typically, the ETL process is carried out by robust enterprise-grade ETL applications such as SQL Server Integration Services (SSIS) or other third-party tools. During the ETL process, data is extracted from a data source, then transformed, validated, standardized, corrected, quality checked and ultimately loaded into a data repository-such as a data mart or data warehouse-where it is streamlined for analysis and reporting. In most organizations, data goes through an ETL (extract, transform and load) process before it is available for reporting.
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