Filtering & Ordering API Update

Made an improvement to allow filtering and ordering on the reports and report run API endpoints. For more information, see the documentation here.

January Bug Fixes

Fixed an issue in which navigating to “Members” panel in Org settings resulted in an error.

Fixed an issue where some users were unable to switch between queries in the query editor.

Fixed an issue where we would prompt users to start their Python and R notebook.

Fixed an issue where improved consistency

Fixed an issue where buttons mistakenly created on white label embeds.

Fixed an issue where a chart would remain in a loading state when navigating between queries.

Improve Admin's Visibility Into Connection Access

It is now possible to manage both member and group access to connections, without having to check group settings separately. When admins need to view who has access to a connection, they can now see the full list of members, even if those members have access through a group. Admins will also be able to contextually view group memberships while managing group access to a connection.


Q3 - Q4 2019 Bug Fixes

  • Fixed an issue where detached values on line charts did not visibly render. They now render as single points.
  • Cosmetic update to the Editor interface
  • Fixed an issue that caused date-filters to be off one day for Central European Time Zones.
  • Fixed an issue in the Report Builder that required users to hard-refresh in order to see updated report filter values. Now filter values immediately update after query-runs.
  • Fixed an issue where long-run Github syncs timed-out. We increased the time-out threshold to compensate.
  • Fixed an issue where the favicon display loading state after the query finished loading.
  • Fixed an issue in the Editor’s navigation panel which caused a query’s name to disappear when being run.
  • Fixed issue where members did not appear in the member search.
  • Fixed an issue that caused some MySQL 8.0+ connections to fail.
  • Fixed an issue with PDF exports where users could not export Big Values with the value 1.
  • Fixed an issue with Redshift that caused excess connections to be created and some statements to fail.
  • Fixed an issue that prevented users from being added to Group.

Connection management

We've improved data source connection management in Mode, giving you the ability to disable automatic schema refresh for a connection. From a connection's page, you can now disable schema refresh, or manually refresh the schema.

To view a connection from your Mode organization, select Organization Settings > Data > Connections and select the data source you'd like to modify.

Group management

We've improved your organization's management of groups. Now, when admins need to add a user to a group, the following options are available:

  • Search for a specific group
  • Search for a user within a group
  • Add or remove users from a group
  • View metadata about a group, including number of spaces and data source connections

To view your Groups, admins can navigate to Settings > People > Groups


Python library version updates

We’ve updated the versions for the following Python libraries:

  • fiona 1.8.8 (currently 1.7.13)
  • geopandas 0.5.1 (currently 0.4.0)
  • hdbscan 0.8.23 (currently 0.8.18)
  • igraph 0.7.1.post7 (currently 0.7.1.post6)
  • keras 2.2.4 (currently 2.2.2)
  • lifetimes 0.11.1 (currently
  • matplotlib 3.1.1 (currently 2.2.3)
  • networkx 2.3 (currently 2.2)
  • nltk 3.4.5 (currently 3.3)
  • numpy 1.17.2 (currently 1.11.3)
  • pandas 0.25.1 (currently 0.23.4)
  • pandas_profiling 2.3.0 (currently 1.4.1)
  • patsy 0.5.1 (currently 0.5.0)
  • pyproj 2.4.0 (currently
  • requests 2.22.0 (currently 2.19.1)
  • scipy 1.3.1 (currently 1.1.0)
  • six 1.12.0 (currently 1.11.0)
  • scikit-image 0.14.3 (currently 0.14.0)
  • scikit-learn 0.21.3 (currently 0.19.1)
  • spacy 2.2.1 (currently 2.0.12)
  • statsmodels 0.10.1 (currently 0.9.2)
  • tensorflow 1.13.2 (currently 1.11.0)
  • urllib3 1.25.6 (currently 1.23)

See the full list of supported Python libraries here

New chart type

We've added a new chart type, called Big Values. Select a Big Value chart to:

  • Visualize KPIs and Trends on top of larger datasets
  • Add additional formatting to customize chart look and feel
  • Apply filters and sort Big Values

For more information on creating Big Values, check out this getting started video.

Answer more questions with Helix

We’ve launched our high performance in-memory data processing system, Helix. Now every query you run in Mode will automatically stream data into our responsive data engine, so that you and your team can visually explore results up to tens of millions of rows.

With Helix, data teams will spend less time on up-front aggregation and calculation — this is no longer a two-step architecture. You can now consolidate multiple queries into one single query to return a larger result set to then slice and dice for additional dimensionality.

Additionally, users can now build reports that rely on filters, rather than parameters for column-specific entries. This reduces database load previously created by parameter use, and empowers a more flexible and fluid report.

Updates to query results sizes

Mode Studio users can view, chart, export, and access the Notebook for query results up to 10 MB.

For Mode Business and Enterprise customers, we offer different plans that support your specific use case. Talk with our customer success team directly to learn more about Helix.

Support for Databricks

We’ve added support for Databricks as a datasource in Mode. To connect to Databricks, first navigate to the Databricks cluster detail page > Advanced Options > JDBC/ODBC tab. Take down the following information:

  • host name
  • port (defaults to 443)
  • database name
  • an authentication token created specifically for your Mode connection (see documentation for more info)
  • the "HTTP path" field

For help finding the settings in the Databricks cluster, check out the Databricks documentation.

In Mode, select Connect a Database in the left hand navigation. In the dropdown list, select Databricks Spark. From there, complete the fields with the above information. Once connected, you can build and share visualizations created on Databricks data.


Please note: users will need to use HiveQL when querying Databricks data in Mode.

If you’d like to connect Mode to a Databricks instance on your internal network, you can use a Bridge Connector.