Advanced data model support with Power Pivot includes a dedicated data modeling editor, a data view, DAX calculated columns, KPIs, and hierarchies. In addition to the basic analytics features, you can use Power Query to import, shape, and merge data from corporate, big data, and cloud data sources, and share queries. Basic data model support allows you to load data to the data model, detect relationships automatically, add time grouping, and create DAX measures.įor more information about obtaining the best performance, see Choose between the 64-bit or 32-bit version of Office.Īdvanced analytics features are available with Microsoft 365 Apps for enterprise, Office 2019 Professional, Office 2019 Professional Plus, and Excel 2019 standalone one-time purchases. With Power Query, you can import, shape, and merge data from files, databases and websites. Such features include PivotTables, slicers, charts and data model capabilities. See the details below for more information on Power Query and Power Pivot availability and ask your IT team if your current Office plan supports these features.įor more information, see Microsoft 365 Apps for enterprise.īasic analytics features are available with any Microsoft 365 subscription or any Office 2016 one-time purchase.
And because I'm using an Excel Table, the table expands to include the new data.īut notice nothing on the chart has changed.Īs before, I need to refresh to update the chart to show the new data.With Microsoft 365 Apps for enterprise, the Excel app on Windows for PCs offers the full Power Query and Power Pivot features that further enhance your analytics and modeling capabilities, take advantage of advanced data connectivity options, and effectively share your data across the organization. On the sheet named "more data" I have sales for March and April and I'll copy and paste that into the data sheet. In short, with Power Query you get your data into Excel, either in worksheets or the Excel Data Model. Use both to shape your data in Excel so you can explore and visualize it in PivotTables, PivotCharts, and Power BI. Power Pivot is great for modeling the data you’ve imported. Power Query is the recommended experience for importing data. You can see we have sales for January and February only. Power Query (Get & Transform) and Power Pivot complement each other. To illustrate, I'll first change the chart to show sales by month. You'll need to follow the same process if you add or remove source data. So remember to refresh the pivot table or pivot chart when data changes.
I'll undo that change to the data, and refresh again to bring the chart back to where we started. Now the sales of shorts is much higher than all the other items. Once I refresh, the new data flows into the chart. To update the chart, you need to tell Excel to refresh the data, and the easiest way to do that is to right click either on the chart or the pivot table, and choose refresh. Notice, nothing that in the chart has changed. I'll change the very first entry on January 1 from $32 to $3200. Now, let me change a value in the source data.
You can see the store sells hats, hoodies, sandals, shorts, and t-shirts. I'll add item on the axis, and then put total into the value area.
So, to start off, let's just see what items are sold.
You can see we have a date, order number, item, total, and state. To demonstrate this, let me create a new pivot chart using this order data from a small online surf shop. When you use a pivot chart, it's important to understand that the chart won't update by itself when source data is added or modified.
In this video, we'll look at how to update data in a pivot chart.