Release Notes

AQL lets analysts build complex metrics much more easily, but learning it takes time. And we know not everyone has that luxury. That’s why we’re building Calculation Builder to let you tap into the full flexibility of AQL, through a point-and-click experience anyone can use.

Why you’ll love it​

Zero coding required: Create, customize, compose metrics with just a few clicks.

Popular calculations: Build count, sum, average, running totals, and conditional metrics effortlessly.

Progressive learning: View the generated AQL behind your GUI calculations to gradually learn the language.

Advanced customization: Convert any GUI metric to AQL for further customization when needed.

Calculation Builder currently supports all basic aggregations (count, sum, average), conditional aggregations (count if, sum if), running totals, and more - all through a simple point-and-click interface.

Share your feedback​

Calculation Builder is currently in beta. We’re still polishing things up, so some behaviors or options may evolve. Your feedback is incredibly valuable - let us know what works, what doesn’t, or what you’d love to see next!

⭐ More calculations are coming up soon.

We’re excited to introduce some fresh functions to enhance your data manipulation. Check them out!

Aggregation Functions​

• corr: corr(table, field1, field2) — Pearson correlation coefficient.
• string_agg: string_agg(expression, sep: separator) — Concatenate expression values.
• percentile_cont: percentile_cont(expression, percentile) — Value at a given percentile (interpolated).
• percentile_disc: percentile_disc(expression, percentile) — Value at a specific percentile (discrete).
• min_by: min_by(table, value, by) — Fetch value from the row with minimum in another field.
• max_by: max_by(table, value, by) — Grab value from the row with maximum in another field.

Time Intelligence Functions​

• date_format: date_format(datetime, format) — Format dates easily.
• from_unixtime: from_unixtime(number) — Convert Unix timestamp to datetime.
• last_day: last_day(datetime, date_part) — Get the last day of a period.

Text Functions​

• find: find(text, substring) — Locate a substring.
• left/right/mid: left(text, length), right(text, length), mid(text, start, length) — Extract from left, right, or mid.
• len/lpad/rpad: len(text), lpad(text, length, pad_string), rpad(text, length, pad_string) — Length, left/right padding.
• lower/upper: lower(text), upper(text) — Change case of text.
• trim/ltrim/rtrim: trim(text), ltrim(text), rtrim(text) — Remove whitespace from sides.
• regexp_extract/match/replace: regexp_extract(text, regex, ...), regexp_like(text, regex), regexp_replace(text, regex, substitute) — Regex operations on text.
• replace: replace(text, old_substring, new_substring) — Replace all occurrences of a substring.
• split_part: split_part(text, delimiter, part_number) — Split text and return a specific part.

Window Functions​

• first_value: first_value(expression) — Value from the first row.
• last_value: last_value(expression) — Value from the last row.
• nth_value: nth_value(expression, N) — Value from the nth row.
• ntile: ntile(n) — Divides rows into ranked groups.
• percent_rank: percent_rank() — Calculates the relative percentile rank of a value.

⭐ Learn more: You can see all AQL functions in our cheatsheet.

Got questions or feedback? We’d love to hear from you! Your input helps us make Holistics better every day. 😊

Your users want more than static charts: they expect to explore, filter, and build. But embedding full BI into your app means weeks of work: auth flows, permissions, versioning, dashboard builders, and visualization plumbing.

Basic embedding doesn’t cut it either. The moment users try to filter, customize, or dig deeper, they hit a wall.

That’s why we built Embed Portal, which allows developers to add a full-featured BI experience directly into their product. You can finally give customers their own space to explore data, create dashboards, and self-serve, all without ever leaving your app.

• Embed a full BI app: Users get a personalized, on-brand environment for exploration, authoring, and dashboard management.
• Self-service UI for end-users: Let users create and edit dashboards with row-level access control.
• Plan-based access: Control data and feature access by subscription tier.
• Build and deploy as code: Manage embed portals in Git, just like the rest of your infrastructure, with versioning and preview support.

Learn more about this feature here: Embed Portal | Bring Self-Service Analytics to Your Customers

Field Promotion allows you to transform your proven ad-hoc calculations into reusable dataset fields, making them easily accessible across all dashboards and reports.

For more details, please refer to our doc.

We’re introducing a simpler, faster way to explore data in Holistics, without the need to write code, tap an analyst on the shoulder, or even build charts by dragging and dropping. You just need to chat with Holistics AI.

Built on top of our governed semantic layer and metric-first query language, Holistics AI is designed to help teams explore data and build charts through natural language, all while staying grounded in trusted, curated datasets.

Holistics AI is currently in development. If you’d like early access and want to help shape how it evolves, you can join the waitlist here.

Here’s a quick look at how it works in action.

What You Can Do With Holistics AI​

• Explore Data (With Thinking): This mode helps you work through complex questions by thinking step-by-step. Holistics AI dynamically builds the logic and fields it needs to answer the data questions.

• Explore Data (Basic Mode): For simpler use cases, Basic mode gives you a fast, code-free way to build visualizations. Just type your question and let Holistics AI pick the fields without needing to drag and drop components or write a single line of SQL.

• Search Docs: Search Docs lets you quickly search and browse documentation without leaving Holistics, so you don’t have to hunt through shared folders or ask your team for links.

TL,DR: What Holistics AI Can Do​

Here’s a quick look at what Holistics AI can do in this upcoming Alpha release:

• Listing: “List all products launched in the last quarter”
• Filtering: “Show transactions over $1000 from new customers”
• Top/Bottom N: “What are our top 5 performing stores by revenue?”
• Metric calculations: “Calculate average order value by customer segment”
• Aggregation and breakdown: “Break down sales by category and region”
• Percent of Total: “What percentage of total revenue comes from each product line?”
• Period Comparison: “Compare this month’s sales to the same month last year”

What’s Coming Next​

Here’s a glimpse of what’s on the way:

• Customize Chart: Make quick adjustments using natural language.
• Explain Chart: Understand trends and patterns through auto-generated insights. We’re building these features to give you more flexibility and clarity as you explore your data.

Want Early Access?​

Holistics AI is in its alpha phase, which means it’s still evolving, and your feedback really matters. It’s already starting to open up new ways to work with data, and we’d love for you to be part of the journey.

If you’re interested in trying it out and helping shape what comes next, join the waitlist and we’ll be in touch.

⚡⚡⚡ Want the full story? Dive into our announcement blog post for all the details! Or read our docs to learn more.

Here's a cool experimental feature that our team hacked together: A Google spreadsheet extension that allows you to self-serve BI datasets directly in Google Sheets.

It works in 4 simple steps

1. Connects to BI environment
2. Let end users self-serve BI datasets (like a pivot table)
3. Sync results directly as google sheets table
4. Set custom frequency for refreshing data

This will be very useful for users who prefer working with spreadsheets, yet need the reliability of a centralized BI system.

Note: This is an experimental project (born out of our recent hackathon). If you’re a customer of Holistics and interested, fill our Early Request Form here and we’ll let you know when it’s available for beta.

We’re excited to announce that our integration with MotherDuck is now available, allowing you to combine the robust, scalable data processing power of MotherDuck with Holistics’ governed self-service platform.

For more information, check out our docs here.

Ever created a running total that worked perfectly in a simple table, but showed gaps when you pivoted by another dimension? We've added a solution for that.

Learn more​

See the full documentation: running_total function reference

Monday morning. Board meeting coming. Your boss needs metrics, and they need it fast. Yet, you find yourself scrolling through cluttered information and interwoven dashboards.

What if you can navigate complex data stories as easily as browsing your favorite website?

This is why we’ve built Tabs for Canvas Dashboards: your data story gets structured and you can break things into neat little sections, like chapters in a book.

Why you'll love it:

• Jump to the right section with one click.
• Group related charts and metrics together.
• Keep filters synced across tabs for a smooth experience.

And yes, your filters stay synchronized across tabs, because continuity matters.

Documentation​

For details, visit our public documentation: https://docs.holistics.io/docs/dashboards/tabs

If you have any feedback for us, share it here. We're all ears!

Data leaders switch from Looker to Holistics for better value-for-money, a more flexible self-service layer, and robust query and modeling capabilities.

But we know migration is never simple.

You've spent months perfecting your LookML models. They contain your business logic, calculated fields, and carefully designed relationships. Starting over feels like building a house twice.

We're removing that barrier.

Coming soon: Our Looker Migration tool that transforms your LookML projects into Holistics' AMQL with just a few clicks. Here's what you'll love:

• Upload your existing LookML project during onboarding
• Watch as we automatically convert compatible elements to AMQL
• Follow our comprehensive migration guides for advanced customizations

No more starting from scratch. No more manual translations of every model and view.

Your data models represent months of work and business logic. Now they can come along for the journey to a more flexible, powerful analytics experience.

For more details, check out our documentation here.