Q2 2023
New features and improvements introduced from April to June 2023
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New features and improvements introduced from April to June 2023
Last updated
Was this helpful?
June 30th, 2023
New Workflows
We have just added a couple of new features in Workflows that are going to improve a lot the explainability of your multi-step analytical pipelines.
Rich notes supporting syntax.
Update nodes with more relevant and descriptive names.
June 30th, 2023
Improvement Workspace
Starting today, users with the ability to customize branding and appearance can also remove the CARTO brand and social icons from their public and embedded maps.
June 27th, 2023
New Builder
This new feature provides advanced capabilities for users to tailor calculations and derive precise insights from their data using SQL Expressions.
With custom aggregation operations, users have the flexibility to define calculations that align precisely with their unique analytical requirements. They can incorporate business-specific formulas and apply complex mathematical operations to single or multiple columns from their data source.
This level of customization empowers users to unlock valuable insights and perform advanced calculations that go beyond standard aggregations.
June 26th, 2023
New Workflows
We have developed a new tool, accessible through the "Draw features" button to define custom geographies as inputs for components.
This new tool come in quite handy in cases where one or more steps in an analysis have to be defined by a manual input, allowing faster prototyping a providing a much better user experience.
June 20th, 2023
Improvement Workspace
When importing geospatial data to a cloud data warehouse, one of the challenges is to select the correct data type for each of the columns in the file, also known as schema. And in most cases, CARTO automatically does the job for you, because we analyze a sample of the data and infer the data type from it.
An example where this new feature is useful is when dealing with postal codes, that depending on the country could be automatically detected as numbers instead of strings — it doesn't make sense to calculate the average postal code.
June 14th, 2023
New Workflows
We have released a new batch of components in Workflows to keep increasing the possibilities and the value of this tool to enable the creation of data pipelines and spatial analyses for our users. The majority of components in this new batch are oriented towards providing more flexibility when manipulating and getting your data ready for the analysis. Here's the list of new components:
Multi-Col Formula: it computes new values based on a given expression and a set of fields to apply the expression to;
Multi-Row Formula: it creates a new table containing a new column computed using a multi-row formula based on one or several input columns;
Find Replace: it finds a string in one column of a table and replaces it with the specified value from another table;
Refactor columns: it refactors the columns in a table, allowing to change names and data types, and to select only certain columns from a table;
Transpose: it rotates table columns into rows;
Text to Columns: it adds new columns based on splitting the text string in a text column;
Unique: it separates unique rows and duplicated rows;
Row Number: it creates a new table with an additional column containing row numbers;
Quadbin To Parent: it adds a new column named quadbin_parent with the value of the parent quadbin at a specific resolution;
H3 To Parent: it adds a new column named h3_parent with the value of the parent h3 at a specific resolution;
H3 KRing: it returns the neighboring indexes in all directions under the K distance size;
H3 Distance: it computes the H3 grid distance between two H3 index column.
June 6th, 2023
New Analytics Toolbox
June 6th, 2023
New Analytics Toolbox
May 16th, 2023
New Builder
Finding your current location on CARTO maps is finally possible. This feature is specially helpful when users require the map zoom in to their current position in a seamlessly manner to obtain insights from their surroundings.
This is how it works:
Click the Focus on User's Device Location button.
Enable Location Services on your browsers if required.
The map display zooms in to your current location and a blue icon indicates your position on the map.
May 8th, 2023
Improvement Workspace
Until this release, it wasn't possible to manage the data available to this connection other than what was already available through Builder and Workflows.
May 5th, 2023
New Analytics Toolbox
May 5th, 2023
New Analytics Toolbox
May 5th, 2023
New Analytics Toolbox
April 24th, 2023
New Builder
SQL Parameters are placeholders that can be used on any SQL Query data source in Builder.
Once defined, the actual value for the parameter can be set through a control UI in the right side panel’s 'Parameters' tab. This allows to manipulate the actual SQL Query through an UI, by both Editor and Viewer users.
Among many different use cases, some applications for this new feature are:
Create 'Text' or 'Dates' parameters.
Reduce the size of a data source before rendering the map.
Allow viewer users to define custom values in the data source in a controlled way.
Use the same parameter in one or more queries.
Filter a dataset before aggregating it to a spatial index grid (H3 or Quadbin).
April 21st, 2023
New Workspace
Developers looking to create geospatial applications at scale usually face an authentication challenge: how to build the application so that data is accessed in a granular and secure way. And there are different solutions depending on your needs: from static API Access Tokens for simple, public applications to dynamic authentication using the CARTO login (with or without Single Sign-On).
Today we're making the creation and management of API Access Tokens much simpler, with a complete user interface to create, edit and delete tokens.
April 13th, 2023
New Workspace
CARTO is the ideal solution for geospatial visualization and analysis of large scale datasets, due to the scalability of the cloud data warehouses (eg: BigQuery, Snowflake, Redshift, Databricks...). However, dealing with such large datasets requires special attention into performance and optimizations.
In just a few clicks, you'll overwrite or generate an optimized copy of your data, that will perform faster and save computing costs.
April 10th, 2023
New Workspace
We are adding two new features for admins to manage new users more easily and predictably:
April 6th, 2023
New Builder
CARTO Builder now supports adding labels to point layers loaded via tiles, with a set of improved features:
Support for primary and secondary label on each point.
Now using a better typography, increasing readability.
Collision control: Now labels are displayed in a way that they don’t collision with each other, adapting dynamically on each zoom level.
Custom colors for the font and outline, allowing much better customization capabilities.
April 3rd, 2023
New Analytics Toolbox
This is a setting that is applied to all maps created in the organization. Additionally, administrators can decide whether new users receive the generic CARTO onboarding materials, to further customize the experience for new users. .
We are excited to introduce the latest enhancement to the in Builder, which allows users to create their own custom aggregation operations.
While working with Workflows, in some occasions a component needs to be defined as a custom geography (point, line or polygon). This is currently the case with "" but this tool will also be used in other components that might need a custom geospatial input.
For those cases where the automatic detection isn't exactly what you need, CARTO now allows you to manually defined the schema of the imported file, both through CARTO Workspace and Builder, and through our .
To read more about how to select a custom schema in your imports, read our .
In the lds module of the last release of the for BigQuery, Snowflake and Redshift we have now added the function to CREATE_ROUTES between given sets of origins and destinations (points) in a query, supporting different transportation modes and other advanced parameters. The function generates a new table with the columns of the input query plus a column with the resulting routes. Note that the routes are calculated by calling one of our external location data services providers. This functionality is also available from CARTO’s .
In the last release of the we have available a new set of functions in order to perform space-time cluster analysis, for when data has both a spatial and a temporal component and you want to identify clusters looking at both dimensions at the same time (e.g. hotspots of demand for food delivery services in different periods of the day). Our implementation computes the space temporal Getis-Ord Gi* statistic for each area and timestamp according to the method described in this . This is supported now with two new functions in the of the toolbox, namely for quadbin indexes and for H3 indexes.
The is a connection that comes pre-created for every CARTO organization, and it's fully managed by CARTO.
Now, all users can introduce a Google account that they'll use to access the console. Once inside, you can run any SQL query, copy and edit existing tables or use other built-in features to import and migrate your data. Read more on .
Users of our have now access to a new module named “statistics” offering functions to compute statistical measures on top of your spatial data. In this last release we have added support for computing the and the Getis-ord Gi* statistics used for the identification of hotspots based on an input feature.
In this last release of the , we have added a new module named “h3” with a set of functions providing users support for operating over the spatial index. H3 is a multi-resolution hexagonal global grid system with hierarchical indexing developed by Uber, offering important benefits when performing spatial analytics at scale. To learn more about Spatial Indexes and H3 in particular, please have a look at our report and our .
Some areas due to their intrinsic characteristics or the data available are not suitable for running the predictive models given the large differences within the data used when training those models (e.g. training a model on big cities and then running predictions in areas of low population density). We have added new functions in the module to allow users to compute the Area of Applicability (AOA) of a BigQuery ML model. It generates a metric which tells the user where the results from a Machine Learning (ML) model can be trusted when the predictions are extrapolated outside the training space (i.e. where the estimated cross-validation performance holds).
In the case of our , this functionality is particularly useful when working with our and procedures of the module.
Learn more about how to set up and use SQL Parameters in your maps .
API Access Tokens are now the recommended method to start working with and the CARTO APIs, and we've updated the documentation and accordingly.
Learn here .
Now, whenever we detect that one of your tables could perform better according to our , we'll show a warning in Data Explorer and Builder, and you'll be able to take action immediately.
To understand in detail how these optimizations work, head to the guide.
Default role for new users: Admins can now choose which role should be applied to new users, and by default it will be set to "viewers" following the least-privilege principle. Find more information about and .
SSO Just-in-time provisioning: Admins that have integrated their own SSO login can now decide whether new users will get additional questions when onboarding or not. If it's enabled, we'll just provision their user as soon as they login, without any needed step. This new setting has been included in the .
In this month's release of the Analytics Toolbox for BigQuery, we have published a new functionality that consists of a set of procedures within the statistics module to enable users to (also known as or indexes) derived from a combination of different features. We have included 3 different procedures:
: to compute a spatial composite score as the residuals of a regression model which is used to detect areas of under- and over-prediction.
: to perform an aggregation of individual variables, scaled and weighted accordingly, into a spatial composite score.
: to measure the internal consistency of the variables used to derive the spatial composite score.
