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Let’s say you are starting at a large data-set with multiple columns. You need to make a pivot report from it for a client or manager. How would you go about it?

This is the exact problem Jo, my wife faced the other day. She came home and after catching up on each other’s day, she asked me how I would do it. That got me thinking. This blog post is born out of that rumination.

Large data-set? Tell me more:

Imagine you have sales data which customer bought products in each city of operation. Say, you have 100s of customers, operate in 50 major cities and sell 16 different products. If you try to make a pivot table with all these fields, you will end up with a monstrosity of 5000 rows. Nobody can read that pivot and make any sense.

What now?

Ideas for creating pivot tables from large data-sets

Here is a list of five ideas to use when you need to create pivot tables from large data-sets.

Idea #1 – Add slicer to one of the fields

Even though you have many fields, chances are the report user wants to focus on one of the elements to start conversation. Add it a slicer. (Related: Introduction to Excel Slicers)

Idea #2 – Show just top values

You can apply value filtering on pivot tables to show just the top performing customer (or product, city etc.). This will greatly reduce the size of your pivot table. You can also collapse a sub-level detail so that user can press + if they want to see details.

To set top 1 filter, simply click on the filter icon on field you want to set it, go to value filters > top 10 and then set it to top 1.

Idea #3 – Individual pivots with drill down option

You can double click on any number in pivot tables to see detail rows that add-up to that number. We can show summary pivot tables from large data-sets instead of full-blown ones. Here is an example.

Idea #4 – Set up support table to show top 3 vs. other view

You can categorize fields like products, customers etc. by introducing an extra table that splits them in to groups. For example, we can categorize products to two types:

• Top 3 products: Most selling products across all our data
• Other products

Once you have such a table, you can connect this product.types table to original data using relationships and then build a multi-table pivot.

Related: How to use relationships to build multi-table pivots in Excel

Idea #5 – Add two-level filtering by alphabets

When using fields like customers or products, you cannot easily apply slicer or report filter on them. This is because such fields have 100s of values usually. One way to reduce the clutter is by introducing two-level filtering.

We can easily do this by adding an extra column to our data to calculate the first letter of customer name. (something like =LEFT([@customer],1) will do.