Release Index
ℹ️ For support, click on the icon on the bottom right. See historical releases
10 Jul 2025 | 01 Jul 2025 | 05 Jun 2025 | 28 May 2025 | 20 May 2025 | 12 May 2025 | 29 Apr 2025 | 10 Apr 2025 | 07 Apr 2025 | 03 Apr 2025 | 25 Mar 2025 | 20 Mar 2025 | 04 Mar 2025 | 25 Feb 2025 |04 Feb 2025 | 21 Jan 2025 | 15 Jan 2025 | 09 Jan 2025
3.15 - 10 July 2025
⚡Actions: Show Toast Message
Use this action to display a toast message in your app when a user interacts with a component (e.g. clicks a button). Great for confirming success, providing tips, or surfacing validation errors, all without custom code.
🧠 Use cases
Writeback: “Please fill out all required fields”
Writeback: “Input successful” / “Form submitted”
Guidance on custom interactions: “Click the chart to drill-down”
Validation error: “Invalid email address”
💡 Tips
Use short, clear language.
“Hide Automatically” is recommended for most info/success messages.
For errors, include details so users can understand what went wrong.
⚡Actions: Switch Case Block
We’ve added a new Switch block for multi-way branching logic; a cleaner alternative to long chains of if-else.
🧠 Use cases
Triggering different actions based on input values
Cleaner logic for menus, states, or modes
Replacing complex nested if-else trees
Here's how it works:
It gets the value of a variable called
num.It then checks that value against several cases:
Case 1: If
numis 1, it will log (or print) "1!".Case 2: If
numis 2, it will log "2!".Case 3: If
numis 3, it will log "3!".
Default: If the value of
numis not 1, 2, or 3, it will execute the default action, which is to log "Default!".
Semantic Layer: Add user feedback, during join quality checks
We've improved the Semantic Layer experience by adding live feedback during Join Quality Checks.
Now, users can see status updates while Astrato calculates the best join path for accurate results and fast queries.
✅ More transparency ⚙️ Smarter join suggestions 🧠 Better decision-making
Scheduled Reporting & notifcations: Extended CRON Scheduling
You can now schedule tasks to run on the last day of each month using standard cron syntax:
🗓️ 0 0 L * * → runs at midnight on the last day
📆 0 0 1,15 * * → still works for 1st and 15th as before
More flexible. More powerful. Fully compliant.
3.14 - 01 July 2025
Export To Excel Enhancements
Exporting data to Excel remains an effective way to share data insights with a broader audience and to save a snapshot of the data, including essential insights.
Exporting to Excel in Astrato got some significant additions:
Export metadata - any export includes an additional sheet with metadata about the export, providing the full query used to generate the data, as well as the user and time of the export.
Providing this information will ensure complete transparency regarding the data origins and simplify returning to the source data by running the query directly at the source.Pivot Table Structure - The exported pivot table retains the structure from Astrato, providing the end-user with the same information in the same perspective as it is displayed in Astrato.
ClickHouse- Dynamic Data Connection
Dynamic data connections increase data security when connecting to ClickHouse.
With this new option, using a single data connection, each user can connect with different credentials or access a different ClickHouse instance.
This feature will enable enforcing row-level and column-level security.
3.13 - 05 June 2025
Actions - Search for Actions in Use
Astrato's actions are powerful tools to build guided analytics and data apps.
This new feature will enhance creator efficiency by reducing the time required to locate and modify actions used in the app.
New Variable Type Date
A new type of display for numeric variables and dates.
The new display type will simplify creators' work to define default values for date variables.
💡When working with actions and date variables, we recommend using the blue blocks for dates, to convert string dates, into proper date formats that are suitable for variables
3.12 - 28 May 2025
Table Columns Enable\Disable - Astrato Action
In guided analytics, it's essential to provide end-users with the ability to drill down and up into the data.
To change the point of view on the data simply and efficiently.
You dynamically control which table columns are included in the underlying data query of the table with simple actions:
Toggle Column – enable/disable a column on user input (e.g. button click)
Disable Column – Disables a column by removing it from the underlying query.
Enable Column – Enables a column by adding it to the underlying query.
💡Get Creative
Combine this with the existing Get user/group block, and build personalized data-driven Data Products without coding!
Predefined Periods - Max and Min Dates
New options in the Date Predefined Periods filter: Min and Max Date.
These new options are dynamic and take into account the start and end dates of a specific field.
These options enhance users' ability to build a dynamic comparison analysis that other users can easily use.
3.11 - 20 May 2025
❄️ ✨ Snowflake Cortex is Now Live in Astrato
Astrato now supports native integration with Snowflake Cortex LLM, giving you direct access to AI-powered insights, without moving a single row of data.
And yes — we’ll be at Snowflake Summit. Come see it live.
⚡ What’s New?
With Cortex in Astrato, you get instant access to plug-and-play LLMs from leaders like Meta, Claude, DeepSeek, and Mistral. Prefer something custom? You can add your own model manually too.
But this isn’t just another chatbot UI bolted onto BI.
Astrato’s semantic layer and query engine work with Cortex to generate smart, context-aware SQL — not guesses. You don’t need to prep data, build pipelines, or handhold the model.
🔒 Why Use Cortex in Astrato?
This is the first BI & Data App platform with in-warehouse LLM control and security.
✅ No data movement
All your data stays in Snowflake — no syncs, no exports.✅ Enterprise-ready
Full RBAC via theCORTEX_USERrole. Built for scale and trust.✅ No-code required
Just click to generate — models understand context via Astrato's semantic layer.
This is AI that fits your governance model, not the other way around.
Table Columns Show/Hide - Astrato Actions
You can now dynamically control visibility of specific table columns with simple actions:
Toggle Column – show/hide a column on user input (e.g. button click)
Show Column – ensure a column is displayed
Hide Column – ensure a column is hidden
💡Get Creative
Combine this with the existing Get user/group block, and build personalized data-driven Data Products without coding!
Font customization - new font choice
Introducing Quicksand, to our family of fonts to choose from. You can set this in your theme (which applies to all objects by default), or separately set this in text-heavy text object, table objects and wordclouds.
3.10 - 12 May 2025
Search for Objects and Variables in Action Editor
Action flows are an essential part of building no-code data apps in Astrato.
The new search capabilities will speed up app flows and simplify working with actions.
Scatter Chart Heatmap Display Mode
Heatmaps help find insights in high-volume data.
For example
Patterns and Trends
Quickly spot high and low values based on color intensity.
Identify clusters of similar values.
Observe gradual increases or decreases across axes (e.g. time, categories).
The new heatmap display mode exposes even more data insights for end-users.
3.9 - 29 April 2025
Native Support for Snowflake Cortex LLM
You can now connect Snowflake Cortex LLM directly to Astrato, giving users secure, in-warehouse AI capabilities with no data movement.
✅ What’s New
Plug-and-play integration with Snowflake Cortex
Support for leading models like:
llama3.1-8bclaude-3-5-sonnetdeepseek-r1
Context-rich model metadata: performance per credit, math reasoning scores, and more
Custom model support via manual entry
🔐 Enterprise Grade Security
Full RBAC alignment using Snowflake's
CORTEX_USERroleCross-region AI access supported
Keeps data within your Snowflake account at all times
💡 Why it matters
Business users now get faster insights, smart measure suggestions, and context-aware generation, all from live data. No prep, no pipelines, just results.
Heatmap Visualization Enhancements
The new features in the heatmap visualization enable better display and explanation of heatmaps, which can tell a more compelling story and reveal additional insights.
The new features include:
Option to place the X-axis labels on top.
Better sorting that maintains individual axes sorting.
Null values styling.
Absolute Function Support
The absolute function can be applied to measures.
Some use cases where the absolute result is useful
Calculating variances or differences
Handling outliers or error values
If you’re flagging data quality issues, you may want to calculate the absolute difference between a value and its target and check if it exceeds a specified threshold.
Aggregating values where negative signs are irrelevant
For example, if you’re summing transaction amounts but only care about total volume, not direction (sales vs returns).
For distance or deviation calculations
In statistical contexts, such as calculating Mean Absolute Deviation (MAD) or Mean Absolute Error (MAE).
Simplifying visuals
If you’re displaying error bars, deltas, or deviations on a chart and don’t want negative numbers cluttering the interpretation
3.7 - 10 April 2025
[Private Preview] Writeback Update Action
A new option to update existing records in tables using the writeback action.
These new options simplify several use cases:
What if scenarios- users can easily make small changes to scenarios
Forecast updates- users can update forecast numbers on the fly.
With these new options, Astrato data apps are more powerful and open more options to act on data insights in a streamlined manner.
If you'd like to join the private preview, you can contact our support.
Advanced Calculation Correlation
A correlation matrix is a powerful data analytics tool that summarizes relationships between multiple variables. It displays the pairwise correlation coefficients (typically Pearson) between variables in a grid format. Here’s a breakdown of the insights you can gain and everyday use cases:
🔍 Insights from a Correlation Matrix
Identify Strong Relationships
High positive correlation (close to +1): Variables increase together.
High negative correlation (close to -1): One increases while the other decreases.
Near-zero correlation (around 0): Little to no linear relationship.
Detect Multicollinearity
When two or more variables are highly correlated (e.g., >0.8 or <-0.8), it can cause problems in regression models by inflating variance.
Feature Selection
You can remove redundant features that are highly correlated with each other, reducing dimensionality without losing much information.
Hypothesis Generation
Spot interesting variable relationships that warrant deeper investigation.
Data Quality Checks
Unexpected correlations may reveal issues (e.g., data leakage, incorrect encodings).
📊 Common Use Cases in Data Analytics
Exploratory Data Analysis (EDA)
Quickly understand how variables relate to each other before diving into modeling.
Financial Analysis
Correlate stock returns, macroeconomic indicators, or portfolio assets.
Marketing Analytics
Correlate customer behaviors, preferences, or demographic features.
Healthcare & Bioinformatics
Analyze relationships between biological markers, symptoms, or patient data.
Sensor or Time-Series Data
Detect correlated patterns across multiple sensors or time-series variables.
3.6.1 - 07 April 2025
Date Picker- Atomic Input Form
A new type of atomic input is from a date picker.
This new form simplifies assigning date values to variables; several use cases became more straightforward with this new option.
Assigning values to variables for period-over-period analysis.
Writeback actions with date input.
Table Cells Actions
Call on actions when clicking or hovering over a table cell.
With these new options, hovering or clicking on a cell can trigger any set of actions.
Use cases supported by this feature:
Show a custom tooltip when hovering over a table.
Writeback a cell or row values when clicking on a cell
Navigate to the detailed view.
3.6 - 03 April 2025
Improved AI Providers' Management
AI features are a core component in Astrato's self-service offering, enabling natural language measure creation and data analysis.
Using the right AI model and prompts for your organization is the best way to get the most out of AI Features.
The new management screen simplifies Admins and creators' ability to define and maintain the right AI provider.
Improved Published Workbook Metadata
When hovering over the published tag of a workbook tile, it shows all the workbook collections.
3.5.1 - 25 March 2025
Drill-Through Dimension in a Table Dimension
Drilling through data is essential to any analytics process that looks for the root causes in data insights.
Tables are another essential part of displaying detailed data for users.
Combining drill-through with a table enhances self-service analytics; it provides end-users with a simple and powerful tool to find data insights.
Send Schedule Reports To External Emails
Schedule reports can be distributed to any email address, including external addresses outside the user's organization.
3.5 - 20 March 2025
Natural Language Measure Generation (AI-assisted) - Public Preview
Self-Service Analytics is about simplifying the data journey from source to insight.
This new capability will allow more users to generate a measure by describing the measure in natural language.
Speed up and simplify measure generation.
Describe the measure and get a suggested result; measure generation includes checks and warnings to ensure the measure's validity.
Easily reuse previous prompts or previously generated measures for small changes.
Pivot Table Selections
A pivot table is one of the most potent tools end-users have to analyze by slicing and dicing the data from different angles.
The new selections allow users to quickly drill down and drill through data.
Selections can be made in one or more dimensions or in a cell, selecting all dimensions that intersect in the cell.
AI Custom Prompts in Insights describe
With the new AI providers, you can now provide custom prompts for the Insights Describe object. Prompts can be entered manually in the property panel or dynamically generated using variables, allowing Astrato actions to adapt based on user interactions.
AI Actions
New actions to use AI to generate insights from a selected chart or responses from a generic prompt.
Combining these actions with existing capabilities helps build tailor-made AI interactions for users.
Actions Improved Help
Actions are powerful tools when building data apps; the improvement helps describe the action block when hovering over it.
This helps lower the level of expertise needed to use this powerful tool.
3.4 - 04 March 2025
🆕 Map Layer - Flow
This map layer is powerful for showing movement patterns, relationships, and connections between geographic locations. Here are some common use cases and data insights that can be derived from such visualizations:
Transportation and Logistics
Flight route analysis: Airlines can visualize their network to identify high-traffic corridors, optimize route planning, and find underserved markets.
Shipping patterns: Cargo companies can track the flow of goods between ports or distribution centers, identifying key shipping lanes and bottlenecks.
Public transit planning: Transit authorities can map commuter flows to understand demand and optimize service frequency.
Migration and Population Movement
International migration: Researchers can visualize immigration and emigration patterns between countries over time.
Internal migration: Governments can track population movement between states or regions to better plan for infrastructure needs.
Refugee displacement: Humanitarian organizations can map refugee movements to coordinate aid efforts.
Business and Economic Analysis
Supply chain visualization: Companies can map their supply networks from raw materials to manufacturing to distribution.
Market expansion: Businesses can identify where customers are coming from to target new market opportunities.
Regional economic interdependence: Economists can visualize trade flows between regions to understand economic relationships.
Communications and Network Analysis
Internet traffic: Network engineers can map data flows between servers and data centers.
Telecommunications: Phone companies can visualize call patterns between cities to optimize network capacity.
Social network connections: Researchers can map relationships between communities or groups.
🆕 New Fonts in visualizations & themes
New fonts are available in Astrato objects. Themes support thew newly added fonts, making it easy to update your fonts in one go.
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If the new fonts are not yet loaded, please conduct a hard refresh.
To hard refresh in Google Chrome on a Windows computer, you can press Ctrl + F5 or hold down Ctrl and click the Reload button. On a Mac, you can press Cmd + Shift + R.
3.3 - 25 February 2025
Excel Template Reporting
Astrato transforms Excel reporting with its live query capabilities, enabling seamless collaboration on financial data. Our BI tool streamlines workflows, allowing users to make real-time adjustments, add commentary, and easily manage approvals. Once finalized, reports can be exported to Excel, complete with the latest data and professionally formatted, all powered by Astrato's continuous live data connections.
Import our new Excel demo workbook to your tenant by clicking on this button below.
Note for BETA users: The Import data and Get Export data from object blocks have been updated for better performance, date handling, and now respecting the column order of tables. If you used the beta version of Excel template reporting, the beta blocks have been deprecated and need to be updated to take advantage of the new improvements.
BETA Notifications and alerting
We are excited to introduce our new Notifications and Alerting feature, currently available in beta. This innovative feature enables you to conditionally trigger notifications for key events, such as new customer sign-ups or when specific thresholds are exceeded.
This beta version is being offered to a select group of customers for initial feedback and testing. If you are interested in participating and exploring the capabilities of our new alerting functionality, please contact our team or your dedicated customer representative to activate it on your tenant.
Leverage Notifications and Alerting to stay informed and responsive to critical business activities.
To participate in the BETA program, reach out to Astrato support.
3.2 - 04 February 2025
Associative Filters
Associative filters allow users to ask new and more advanced business questions that use the association between different entities in the data.
Here are some examples of business questions:
Find the customers who bought Product A and not Product B
Find products that were sold this month in store A or sold last month in store B
Find employees who know how to code both in Python and SQL
When an associative filter is applied, the user can still see all the information about the filtered population, unlike regular filters that reduce the information to the specific question asked.
Associative filters allow users to ask advanced business questions intuitively.
Users can easily edit the filter and save them for repeated usage.
3.1 - 21 January 2025
Stacked Bar Chart Data Label
A stacked bar chart can highlight multiple layers of insights.
Comparison between the total height of each stacked bar
Comparison of the bar inside each bar and the overall stacked bar height share.
For example, what was the revenue each quarter splitter by customer type?
This chart shows the overall revenue trend and the significance of each customer type in each quarter. It also tracks changes in the different types' significance over time.
The new settings allow users to define which information will be presented on the bars.
There are three options:
Value- show the bar value
Share- show the bar share out of the total stacked bar value
Combined- show both value and share.
3.01 - 15 January 2025
AI Insights Improved Display
AI insights are now easier to read and finding insight.
AI insights help users find insights in a dashboard or specific visualization.
Vertical Display For Gauge Chart
Gauge Charts are good when comparing performance against targets for multiple entities.
With the new display, more intuitive gauge charts can be created.
3.0 - 09 January 2025
🆕Workbook Development Life-Cycle (Workbook Versions)
Workbook development reimagined with the introduction of workbook versions,
The creators work is simplified and improved.
Here are the key benefits of the Workbook Life-Cycle (Versioning) feature:
Effortless Version Logging: Easily log and describe each version for clear documentation.
Quick Recovery: Restore previous versions to mitigate disruptions from errors.
Flexible Publishing: Unpublish and republish workbooks with different versions for better control.
Version Consolidation: Unified view of drafts and published versions to reduce clutter.
Enhanced Collaboration: Merge drafts and manage versions across workbooks for effective teamwork.
Rollback for Safety: Revert to earlier published versions for stability and data integrity.
Streamlined Migration: Simplified transition to the new versioning system.
Advanced Chart Calculation- Percentile
The percentile function is a valuable tool in data analytics, providing a deeper understanding of data distribution and supporting robust decision-making. Here are the primary benefits of using it:
Improving Decision-Making
Percentiles help organizations make informed decisions, such as identifying top-performing regions, products, or services, by providing a clearer view of data characteristics.
Example Application
If you’re analyzing employees' salaries in a company:
The 10th percentile might represent the lower earners.
The 90th percentile could represent top earners.
This information could be used to evaluate pay equity or design compensation policies.
Other benefits of using percentile in the analysis are:
Understanding Data Distribution
The percentile function helps divide data into 100 equal parts, offering insight into how data points are spread across a range. For instance, the 25th, 50th, and 75th percentiles (quartiles) show the spread of the dataset's lower, middle, and upper sections.
Identifying Outliers
Percentiles are crucial for detecting outByning by analyzing data points below the 1st or above the 99th per, analysts can flag anomalies needing special attention or cleaningcentile.
Comparing Relative Performance
Percentiles allow comparison of a value's position relative to the dataset. For example, a student's score in the 90th percentile means they performed better than 90% of their peers.
The percentile function is essential for summarizing, interpreting, and applying data insights effectively.
The percentile function is available in these advanced calculations:
Total- calculate the selected percentile of the dataset
Compare to total- compare entity values to the chosen population percentile value
Nested calculation- calculate the selected percentile value for a defined dataset.
Big Data Analysis - Extend Queries Runtime
This is a new option for extending the running time of queries, which is essential for data analysts and report creators working with large datasets.
The new options allow users to extend the queries running time to handle long-running queries.
Improved table Filtering
Users can filter table dimensions by using range selections for numbers and dates.
The new option to apply range filtering directly in the table enhances the simplicity of asking business questions in Astrato.
