What's New

You can now export entire dashboards directly to Excel! 🎉

This update is designed to saves you time and effort, letting you download your dashboard as a single Excel file in just a few clicks.

Level Up Your KPIs with New Styling Options ✨ 🌟 😍

With our new styling options, you are now empowered to make your KPIs more visually impactful. Adjust font size, font color, text alignment, and explore unique styles for each comparison type 🙌

Ready to give your KPI Metrics a dazzling makeover? Share your styling creations with us! ✨🎉

Introduction​

AQL is getting an upgrade! No more static calculations. You can now make AQL dynamic by combining it with Query Parameters.

This means AQL definitions can adjust based on user inputs via the Dashboard Filter, and you'll be able to do Dynamic fields selection (dynamic dimensions, dynamic metrics)

Demo​

Dynamic Dimensions Selection​

Dynamic Metrics Selection​

More details on how to set up​

If you want to understand more details on how to set up this, please refer to our doc about Advanced Use Cases

Say goodbye to the hassle of manually resolving merge conflicts!

We’re thrilled to introduce the Quick Resolve option, which allows you to:

• Instantly choose whether to keep your version, or the incoming version for each conflicted file.
• Apply your choice to all files at once, so you can quickly return to your tasks.

For those who prefer a more hands-on approach, the Manual Resolve option remains available, letting you sort out the conflict in the code editor.

Check it out in action:

We’ve made working with tables easier and more intuitive! With these updates, you can now:

• Change aggregations and time grains
• Auto-size columns
• Rename columns
• Remove columns

All directly on your tables, giving you more control and flexibility in your workflow.

Give it a try and let us know what you think! 😊

Holistics now supports two-factor authentication (2FA) for password-based login.

Two-factor authentication (2FA) adds an extra layer of security to your Holistics account. Once enabled, it requires an additional code from an authenticator app (e.g., Authy, Google Authenticator, etc.) along with your email and password, ensuring only you can access your account.

The admin can require two-factor authentication for all users to enhance the organization’s security.

To learn more, please go to Two-factor Authentication for detailed settings.

Stop duplicating the same filter logic across every metric in your exploration. AQL Condition lets you define filtering criteria once and apply it to all your metrics automatically.

Why this feature?​

When building explorations, you often need to apply the same complex filter to multiple metrics. Previously, you had to add where() clauses to every single metric, leading to repetitive code and maintenance headaches. If you needed to change the filter logic, you'd have to update it in multiple places.

Now you can define your filtering logic once in the explore's filters block, and it automatically applies to all metrics.

How it works​

AQL Condition uses the same expression syntax as the where() function's condition parameter, but you define it at the exploration level instead of repeating it for each metric.

Before vs After​

Before (Repetitive filtering)

explore {
  dimensions {
      // your_dimensions
  }
  measures {
    orders: total_orders | where(users.gender == 'female' or countries.name == 'Vietnam'),
    revenue: revenue | where(users.gender == 'female' or countries.name == 'Vietnam'),
    users: total_users | where(users.gender == 'female' or countries.name == 'Vietnam')
  }
  filters {
    // your_condition
  }
}

After (Single filter definition)

explore {
  dimensions {
      // your_dimensions
  }
  measures {
    orders: total_orders,
    revenue: revenue,
    users: total_users
  }
  filters {
    users.gender == 'female' or countries.name == 'Vietnam'
  }
}

This approach makes your code cleaner and easier to maintain, while ensuring consistent filtering across all metrics.

Learn more​

See the full documentation: AQL Condition reference

For making conditions dynamic with dashboard filters, see: Dynamic Conditions

In a time-series report, you may want to group data by different time intervals such as Day of Week, Day of Month, Month of Year, Hour of Day, etc.

Previously, you had to write AQL expressions to extract such date parts from dates. Now, our Date Parts feature helps you easily extract these specific types of dates from time dimensions so that you can slice your data under different time lenses.

For more detailed examples, please refer to this document:

• Extract date parts from dates

For trend lines and reference lines, in addition to the toggle break down by legend, you also have another toggle, merge into one line, which helps visualize a single global line despite the legend.

Although both toggles produce the same result of one single line in the chart, their calculations differ:

• Turning off “break down by legend”: This calculates the trend line or reference line based on the total values (i.e., not segmented by legend).
• Turning on “merge into one line”: This calculates the trend line or reference line based on the segmented values.

For more detailed examples, please refer to these documents:

• Trend Lines: Display one or multiple trend lines
• Reference Lines: Display one or multiple reference lines

The Validation API allows you to validate your projects outside of Holistics, enabling smooth integration with CI/CD workflows. This feature is particularly useful in scenarios such as:

• Validating updates before merging a pull request into the master branch by incorporating the Validation API within the CI/CD pipeline.
• Validating changes immediately after updates are pushed to the master branch.
• Running validations prior to using the Publish API to ensure a successful publish.