Pivot Table

Transform your data into a pivot table to gain meaningful information by grouping, aggregating, and filtering data

The pivot table layout in Noloco collections enables you to transform your data into meaningful summaries. With this feature, you can group by multiple columns, aggregate multiple values, and define rows for comprehensive data analysis. You can also filter your data just like any other collection layout, making it perfect for in-depth analysis.

Pivot Table layouts are only available on the Pro, Business and Enterprise plans For more information view our Pricing Page

What is a Pivot Table?

A pivot table is a powerful tool for summarizing data. It allows you to reorganize and summarize selected columns and rows to create customized reports. By grouping, aggregating, and filtering your data, pivot tables help you analyze patterns, trends, and insights more effectively.

Setup a Pivot Table

Setting up a pivot table in Noloco is straightforward. Follow these steps to transform your data into a pivot table for better analysis:

1. Navigate to Your Collection:

   Open the Noloco app and go to the collection you want to convert into a pivot table.

2. Choose Pivot Table Layout:

   In the Layout options select 'Pivot Table' from the available options.

3. Configure Columns:

   Select the columns you want to group by. You can choose multiple columns for hierarchical groupings.

4. Define Rows:

   Select the fields that will form the rows of your pivot table. This determines how your data will be categorized and displayed.

5. Select Values:

   Define the aggregation method for each value, such as sum, average, or count, depending on the type of analysis you need.

Example Pivot Tables

Here are three examples of how you can set up a pivot table in Noloco and the insights you can gain from each configuration:

Example 1: Sales Data Analysis

Data Set: Monthly sales data for various products across different regions.

Setup:

• Columns: Region

• Fields: Product

• Values: Sales Amount (Sum), Sales Quantity (Count)

This pivot table helps you understand which regions are performing best in terms of sales. By grouping by region and breaking down the sales amount and quantity for each product, you can identify top-selling products in each region and compare regional sales performance.

Example 2: Employee Performance Evaluation

Data Set: Employee performance metrics across different departments.

Setup:

• Columns: Department

• Fields: Employee Name

• Values: Performance Score (Average), Completed Projects (Sum)

This pivot table allows you to evaluate employee performance within each department. By averaging performance scores and summing up the completed projects for each employee, you can identify high-performing employees and departments, helping in performance reviews and resource allocation.

Example 3: Customer Support Metrics

Data Set: Customer support tickets with details on resolution times and ticket statuses.

Setup:

• Columns: Ticket Status

• Fields: Support Agent

• Values: Resolution Time (Average), Number of Tickets (Count)

This pivot table provides insights into customer support efficiency. By grouping tickets by status and analyzing the average resolution time and the number of tickets handled by each support agent, you can identify agents who are resolving tickets quickly and those who may need additional support or training.

FAQs

What types of data can I use in a pivot table? You can use any type of data stored in your Noloco collections, including numeric, textual, and date/time data.

Can I apply filters to my pivot table? Yes, you can filter your data in a pivot table just like any other collection layout, allowing for more focused analysis.

Q: Can I export the data from my pivot table? Noloco does not currently support direct export of pivot table data, but you can export the underlying collection data and recreate the pivot table in external tools if needed.

Are there any limits to the number of columns, fields, or values I can use in a pivot table? Yes, you can have up to 3 columns, and only one row and one value altogether.