Power Query, in Microsoft 365, empowers users to transform data easily without IT assistance, combining sources, cleaning, and reshaping data without coding.
Large Datasets: Power Query is well-suited for handling large datasets, as it performs transformations directly on the source data before loading it into Excel. This can help improve performance and reduce memory usage compared to Excel formulas.
What is Power Query? Power Query is a data preparation and transformation ETL engine that lets you connect to various data sources. Power Query is available in Microsoft Excel, Power BI, Power BI dataflow, Azure data factory wrangling dataflows, SQL Server Analysis Services, and much more.
In summary, Power Query helps users solve the problem of cleaning messy data by providing a set of tools and features that make it easier to extract, transform, and load data in Excel.
With Power Query (known as Get & Transform in Excel), you can import or connect to external data, and then shape that data, for example remove a column, change a data type, or merge tables, in ways that meet your needs. Then, you can load your query into Excel to create charts and reports.
Power Query is a powerful data connection technology available in Microsoft Excel and Power BI, designed to facilitate data discovery, access, and collaboration. It allows users to import, clean, and transform data from various sources and then load it into Excel worksheets or Power BI data models for analysis.
Connect to SQL Server database from Power Query Desktop
Select the SQL Server database option in the connector selection. In the SQL Server database dialog that appears, provide the name of the server and database (optional). Select either the Import or DirectQuery data connectivity mode (Power BI Desktop only).
When you create a new transformation step by interacting with the components of the Power Query interface, Power Query automatically creates the M code required to do the transformation so you don't need to write any code.
It is found in software such as Excel, Power BI, Analysis Services, Dataverse, Power Apps, Azure Data Factory, SSIS, Dynamics 365, and in cloud services such as Microsoft Dataflows, including Power BI Dataflow used with the online Power BI Service or the somewhat more generic version of Microsoft Dataflow used with ...
Power Query is available as a free add-in on Excel 2010 and 2013, which you can download from Microsoft's website.
Large data sources and data retrieval: Power Query
Power Query is specially designed for data retrieval, transformation, and combination tasks. When you need data from one of those sources, Power Query gives you a no-code way of bringing that data into Excel in the shape you need.
Conclusion. While traditional Excel functions are invaluable for specific scenarios, Power Query significantly extends Excel's capacity, particularly for handling large or complex datasets. Mastering both tools allows you to create efficient, scalable, and robust data analysis workflows in Excel.
Power Query is the data connectivity and data preparation technology that enables end users to seamlessly import and reshape data from within a wide range of Microsoft products, including Excel, Power BI, Analysis Services, Dataverse, and more.
Pros of Power Query include user-friendliness, time-saving, reusability, flexibility, and integration, while cons include performance issues with large datasets, limited functionality, and compatibility issues with other data analysis software.
Advanced Power Query Techniques
Power Query formulas, also known as M language expressions, allow users to perform complex data transformations. These formulas can be used to create custom columns, manipulate text, perform calculations, and more.
Any such data mashup is expressed using the Power Query M formula language. The M language is a functional, case sensitive language similar to F#.
If you've ever worked with large datasets in Google Sheets, you know how quickly things can get out of hand. Sorting through rows upon rows of information isn't just tedious; it can be downright overwhelming. That's where Power Query comes into play—not just in Excel but also in Google Sheets.
If you're wondering how to execute SQL query in Excel, you can use the Power Query feature. Navigate to the Data tab, select Get Data > From Database > From SQL Server Database. Enter your server and database details, and then write your SQL query in the advanced options. This will import the query results into Excel.
You can enter data into a Microsoft Excel sheet or run a bit of M code in Microsoft Excel Power Query when you need to create a table.
Power Query is just ONE automation tool. It's a great one but there are others you might be missing out on just because you don't know of them, or you haven't dared explore them. This course will shine a light on the other tools as well. You'll get to automate what comes before and after Power Query.
Select a query management command: Edit Edits the query in the Power Query Editor. Only available on the Queries tab of the Queries & Connections pane. Delete Removes a query.
Using Power Query for ETL
Power Query is primarily used to get data (extract) from data sources like Excel, Sharepoint, or SQL Server. Power Query also allows users to aggregate, append, and transform data before it's loaded into Power BI for visualization.