How to Narrow Down Engineering Metrics Using Keypup's Filters

Discover how to use Keypup's filtering feature to narrow down metrics and gain more accurate insights into your development process. Create custom reports and make data-driven decisions that will help your organization succeed.

Celine Nabais
Celine Nabais LinkedIn
β€’ 2 min read
How to Narrow Down Engineering Metrics Using Keypup's Filters

As a tech leader, you know that data analytics is essential for making informed decisions and driving improvements in your software engineering organization. However, having access to a large amount of data doesn't necessarily mean you have the insights you need to make the right decisions. This is where filtering comes in handy. By applying filters to your data, you can narrow down the metrics to focus on specific areas such as time frames, projects, teams, labels, or individuals. This can help you gain more accurate insights into the development process and identify areas for improvement.

For example, let's say you want to analyze the performance of your development teams. By filtering the metrics to focus only on the developers who worked on a specific project, you can gain a more accurate understanding of how that team is performing. You can identify top performers, areas for improvement, and potential roadblocks that are preventing the team from reaching its full potential.

In this tutorial, we'll show you how to narrow down metrics using Keypup's filters. Keypup provides a variety of engineering metrics, reports, and KPIs to help you get started. These templates are built using default filters that you can easily adjust to best suit your needs. We understand that every software engineering organization is unique, so we haven't hardcoded the provided templates.

Remember, if you have any doubts or if you are not sure which fields are available, you can always use the dropdown menu or use the β€œhelp” button located at the bottom right of your screen.

Here are the steps to narrow down metrics using Keypup's filters:

‍

1. Select the insight you want to modify by clicking on the edit button located on the top left of the insight. In this case, we're modifying the PR Lead Time for Changes metric.

Image

2. Select "Edit insight" from the dropdown menu.

Image

3. On the configuration panel located on the left side of your screen, select the "Configure table" option.

Image

4. Click on the "Configure filter" button located at the top right of the configuration panel.

Image

5. This template has two filters applied by default, the item type (Pull request/Issue) and the merge date time frame (past 12 months). These filters can be amended to best suit your needs. For this example, we'll click on the "+ Add rule" option.

Image

6. We'll narrow down the metric to a specific user by clicking on the dropdown "Is me".

Image

7. You have multiple ways to include or exclude information to best illustrate your use case. In this case, we'll use the sign = as we know which user we want to report on.

Image

8. We can then paste or type in the user name.

Image

9. Click on the "Apply filters" button to see the narrowed result.

Image

10. Once done, click on the "Save" button located at the top right of your screen.

Image

Filtering is a powerful tool for data analytics in software engineering organizations. By narrowing down metrics to focus on specific segments, you can gain more accurate insights into the development process and identify areas for improvement. Whether you want to analyze the performance of a specific team, identify top performers, or pinpoint potential roadblocks, filtering can help you get the insights you need to make informed decisions and drive success.

With Keypup's platform, you can easily adjust the default filters to fit your unique needs and create custom metrics and reports without having to start from scratch. By leveraging the flexibility and customization of Keypup's filtering feature, you can gain more accurate and meaningful insights into your development process and make data-driven decisions that will help your organization succeed.

Try Keypup's platform today to see how you can benefit from using filters to narrow down your metrics and create custom metrics and reports for your organization.

Ready to Transform Your Analytics?

Join teams already using AI to make data-driven decisions faster than ever.

Most Recent Articles

The Bug SLA Mirage: Why Priority Fix Targets Are Missed and Nobody Knows

The Bug SLA Mirage: Why Priority Fix Targets Are Missed and Nobody Knows

Your bug SLA report says 91%. Your customers experienced 65%. Learn what engineering leaders on Reddit say about P1 fix-time targets, SLA clocks that start late and bugs closed to stop the timer at enterprise scale, and how Keypup MCP measures real SLA attainment by priority and team from Jira workflow history and linked pull requests.

Thomas Williams
The Dependency Bot Backlog: Why Dependabot and Renovate Pull Requests Pile Up Unmerged

The Dependency Bot Backlog: Why Dependabot and Renovate Pull Requests Pile Up Unmerged

Dependabot and Renovate open thousands of pull requests across enterprise repositories, and most of them are never merged, merged with no review, or left open for months. Learn what engineering leaders on Reddit say about dependency bot noise, unowned major upgrades and auto-merge risk, and how Keypup MCP measures the bot backlog by version bump, ecosystem, merge path, next action and owner.

Liam Davis
The Vendor Black Box: How to Measure Outsourced Engineering Teams with Git and Jira Data

The Vendor Black Box: How to Measure Outsourced Engineering Teams with Git and Jira Data

Enterprises spend millions on outsourced and offshore engineering vendors, yet most can only measure them through hours billed and status reports. Learn what engineering leaders on Reddit say about vendor black boxes, hidden review load and untraceable work, and how Keypup MCP compares vendor and in-house pull requests, review wait times, review load and Jira traceability to show what each vendor actually delivers.

Stephane Ibos