Release Notes

We’re excited to share that you can now undo and redo your filter actions while exploring dashboards.

✨ What's new​

• Undo/Redo for filters: Previously, only drill-downs and break-downs were reversible. Now, every step of your analysis — from filtering to drilling down — can be undone or redone, giving you more freedom to explore without worry.
• History view: Right-click on Undo or Redo to see your complete exploration history at a glance.

We've improved the relationship list view to make it much easier to understand your data model connections at a glance.

When reviewing relationships—especially in complex data models—it can be challenging to quickly distinguish between model names and field names. We've added visual indicators to help you parse this information more efficiently.

✨ What's New​

• Field type icons — Each field now displays an icon indicating its data type, making it easier to understand the relationship at a glance
• Visual separation — Model names and field names are now clearly differentiated with color coding, where model names appear in a lighter gray while field names stand out in bold
• Better scannability — The improved layout helps you quickly navigate through long lists of relationships without getting lost in the text

🎯 Benefits​

This enhancement is particularly helpful when you're working with unfamiliar data models or need to quickly verify relationship configurations across multiple tables. The visual cues reduce cognitive load and help you spot patterns or issues more quickly.

📸 Before and After​

Before:

After:

When a user clicks "drill down" or "break down," the default dimension list displays all available dimensions from the dataset. Holistics allows you to customize this dimension list to enhance your users' experience.

For example, you can highlight the most relevant dimensions and organize them into groups such as Locations, Products, and User Demographics as shown in the video below.

See details of how to customize it here: Drill down & Break down | Customize the dimension list

When viewing underlying data, the default table shown may not always be relevant to users' needs. Now, you can ​​customize different views of the underlying data​ to enhance your users' experience.

In this example, when examining the underlying data for the Revenue metric, users can select from different views, such as Orders, Users, or Products.

See details of how to customize it here: View underlying data | Customize the underlying views

We’re thrilled to introduce our upcoming feature - Default dashboard template! 🎉 🎉

This feature is designed specifically for admins who need to enforce brand standards and best practices across their entire organization.

What’s New​

• Before: New dashboards automatically inherited the base Holistics look, meaning users had to manually spend time aligning new dashboards with your structural and brand requirements.
• Now: Admins can define one master template that is automatically applied to every new dashboard created.

This guarantees organizational consistency from the moment a user starts building their dashboard.

How to set the default dashboard template​

Step 1: Create a template: A dashboard template can include:

• Visual styling (themes, colors, branding)
• Structured layouts and pre-configured components
• Defined block interactions, and much more.

Step 2: Set the default template: Once marked as the default, this template will be automatically applied to all new dashboards across the organization.

Documentation​

To be updated.

Timeline​

You can expect the first release to be available by late October 2025.

We hope this feature gives you the governance and speed you need to scale dashboard creation confidently. We can’t wait to hear what you think! 😊

Keeping your workspace clean is important, but determining which content is actually unused is the challenging part. We are excited to introduce Archive Recommendations, a smart feature that automatically identifies inactive content so that you can archive with confidence.

⭐ What's new?​

Archive Recommendations analyzes your workspace and surfaces content that shows signs of being ready for archiving:

• Dashboard: No views in the last 30 days
• Dataset: No direct views or no connected dashboard views in the last 30 days.

For more information, check out our public docs: Archive Recommendations

⌛ Timeline​

• released Archive recommendations for dashboards
• upcoming Archive recommendations for datasets (Est. Mid Oct)

Hi everyone,

Great news, the Merge Request workflow for GitLab has officially been released.

This is a new feature that brings our PR Workflow goodness to GitLab MRs so you can review, approve, and ship analytics changes using the process your team already knows.

What you will get:

• ⚡ One-click MR creation from Holistics, with AI to draft the MR title and description.
• 🔈 Live MR status inside Holistics — no more tab-hopping to GitLab.
• 🔀 Auto-publish on merge: when an MR is approved and merged into your master branch, the changes publish themselves.
• 👀 Better visibility and control over changes, helping keep data reliable and audits painless.

If your team runs on GitLab, this will make reviews smoother, governance tighter, and shipping safer — without changing how you work.

For more details, please refer to our doc Set up Merge Request Workflow (for GitLab)

Have you ever received JSON data in your dataset and wished you could unnest it right there, without having to go back and modify your data model?

Previously, you'd need to:

• 🔙 Navigate back to the model
• 🛠 Create a SQL dimension
• ✍ Write custom SQL just to extract fields

Why? Because AQL doesn't yet have built-in support for these database-specific functions (like JSON unnesting).

Now, with SQL Passthrough for AQL, you can do this directly in your dataset! 🎉

No more back-and-forth — just write AQL and leverage native SQL functions to handle JSON (and much more).

This isn’t limited to JSON unnesting — any database-specific functionality not available in AQL can now be tapped into using passthrough.

👉 How it works: SQL Passthrough functions act as a bridge, letting you call native SQL functions from your underlying database while maintaining type safety inside AQL queries.

That means you can:

• Extract fields from JSON directly in your dataset
• Apply database-specific functions (Postgres, BigQuery, MySQL, etc.)
• Extend the power of AQL without breaking your workflow

For more details, you can visit our public doc about SQL Passthrough

We're excited to announce Layout Assist, a new setting designed to make your dashboard editing experience easier and more intuitive.

Here's what's included:

• Prioritize Non-overlap: Now you can set your blocks to auto avoid overlapping. To switch to overlay mode, just press and hold a block for two seconds.
• Trim whitespace to remove extra space around your elements.
• Shift multiple blocks at once for faster adjustments.
• Auto-expand the canvas as you add new blocks.

We hope these updates streamline your workflow and make dashboard editing a breeze. We can’t wait to hear what you think! 😊

Timeline​

This feature is rolling out gradually over the next two weeks. If you want to try it out right away, just let us know and we’ll enable it for you.

Ever wanted to adjust a filter on a single chart—say, switching Status from WIP to Done—but there wasn’t a filter control ready for you?

Now you can!

✨ What's new​

Filter Visualization Directly on the Dashboard: You can now apply filters to any widget right from the dashboard. No need to pre-create filter controls or open the full data exploration. There are two ways you can do that:

• Filtering through the visualization action bar

  Expand

• Use the table context menu

  Expand

🎯 Benefits​

• Better self-service for business users: You can quickly adjust the filter, no learning curve required.
• Stay in context: Adjust filters right on the dashboard while still interacting with drill-downs, cross-filtering, and other widgets
• Less setup for builders: Dashboard creators no longer have to prepare every filter in advance.

📝 Notes​

• Available for Holistics 4.0 users only
• Requires Explore permission on the widget’s dataset