Pivot tables are one of the most powerful and useful features in Excel for data analysis and reporting. They allow you to quickly summarize, organize, and extract insights from large datasets. Pivot tables make it easy to explore different views of your data by dragging and dropping fields to change what gets summarized and filtered.
To create a basic pivot table, you first need a dataset with your source data in a spreadsheet or table format. The dataset should have column headers that indicate what each column represents, such as “Date”, “Product”, “Sales”, etc. Then select any cell in the range of data you want to analyze. Go to the Insert tab and click the PivotTable button. This will launch the Create PivotTable dialog box. Select the range of cells that contains the source data, including the column headers, and click OK.
Excel will insert a new worksheet and paste your pivot table there. This new sheet is known as the pivot table report. The left side of the sheet will show fields available to add to the pivot table, which are the unique column headers from your source data range. You add them to different areas of the pivot table to manipulate how the data gets analyzed.
The most common areas are “Rows”, “Columns”, and “Values”. Dragging a field to “Rows” will categorize the data by that field. Dragging to “Columns” will pivot across that field. And dragging to “Values” will calculate metrics like sums, averages, counts for that field. For example, to see total sales by month, you could add “Date” to Rows, “Product” to Columns, and “Sales” to Values. This cross tabs the sales data by month and product.
As you add and remove fields, the pivot table automatically updates the layout and calculations based on the selected fields. This allows you to quickly explore different perspectives on the same source data right in the pivot table report sheet without writing any formulas. You can also drag fields between areas to change how they are used in the analysis.
Some other common ways to customize a pivot table include filtering the data through the pivot table field list area on the right side. Simply clicking on a category under a field in the list filters the whole pivot table to only show that part of the data. This allows you to isolate specific areas you want to analyze further.
Conditional formatting capabilities like highlighting Cells Rules can also be applied to cells or cell ranges in pivot tables to flag important values, outliers and trends at a glance. Calculated fields can be created to do math functions across the data to derive new metrics. This is done through the PivotTable Tools Options tab.
Pivot tables truly come into their own when working with larger data volumes where manual data manipulation would be cumbersome. Even for datasets with tens of thousands of rows, pivot tables can return summarized results in seconds that would take much longer to calculate otherwise. The flexibility to quickly swap out fields to ask new questions of the same source data is extremely powerful as well.
Some advanced pivot table techniques involve things like using GETPIVOTDATA formulas to extract individual data points from a pivot table to incorporate into other worksheets. Grouping and ungrouping pivot fields allows collapsing and expanding categories for abstraction levels. Using Slicers, a type of Excel filter, provides an interactive way to select subsets of the data on the fly. PivotCharts bring the analysis to life by visualizing pivot table results in chart formats like bar, column, pie and line graphs.
Power Query is also a very useful tool for preprocessing data before loading it into a pivot table. Options like transforming, grouping, appending and aggregating data in Power Query clean rooms provide summarized, formatted and ready-to-analyze data for pivoting. This streamlines the whole analytic process end-to-end.
Pivot tables enable immense flexibility and productivity when interrogating databases and data warehouses to gain insights. Ranging from quick one-off reports to live interactive dashboards, pivot tables scale well as an enterprise self-service business intelligence solution. With some practice, they become an indispensable tool in any data analyst’s toolkit that saves countless hours over manual alternatives and opens up new discovery opportunities from existing information assets.