Release Overview: March 2021

Aunalytics is excited to announce the March 2021 Daybreak release to our clients. This release will provide clients with model and site enhancement information along with any fixes to existing functionality we have included.


Natural Language Answers

Daybreak exists to provide answers to the questions users of all backgrounds have about their organizations' data. Now, thanks to months of research and development, Aunalytics is excited to debut a new tool that puts data within the reach of everyone: natural language answers. Natural language answers is a machine learning service that enable users to interact with their industry intelligent datamarts by simply asking questions.

Natural language answers integrates into the Daybreak web app to provide users a way to get answers from their datamarts as easily as typing a question in the Google search bar. Behind the scenes, Aunalytics' proprietary NL2SQL technology translates these questions into structured queries to deliver datasets that respond to questions a user might ask.

nl answers screenshot

Aunalytics' Innovation Lab data scientists have created a machine learning algorithm to understand the questions people ask about their data in a particular focus industry so that it can translate those requests into structured queries suitable for running against a SQL-compliant datamart.

Thanks to these efforts, our clients using Daybreak for the financial services industry can now begin the day with answers by asking Daybreak questions like "give me a list of mortgages opened last quarter" or "Show me CD accounts with a maturity date in the next month."

Learn more about this exciting new feature and how to use it here.


Daybreak Insights provide a new way to extract value from data by allowing the creation of dashboards of visualizations from the results of their datamart queries. With this release, users will be able to access the "Insights" tab in the Data Builder's results area (at the bottom of the Data Builder tool). The Insight's tab provides a dashboard where users can create, save, and share charts of their query's results.

Currently, four types of visualizations are supported: numerical summaries, column charts for data points grouped by category, line charts for data points grouped by time interval, and donut charts to show proportional distribution by category.

insights demo

Learn more about Insights and start creating them today here.



Datamarts are new analytics cloud management components for the Aunsight platform designed to support the needs of our Daybreak industry intelligent datamarts and web app. Datamart objects provide a single point of configuration for defining the structure and schema for the data that will be exposed in a Daybreak datamart. This new component allows solutions engineers to define the way data will be presented in a datamart and enable other components such as Workflows and Connectors to copy and transform data into it according to the rules defined for it.

Solutions engineers can now begin to implement datamarts to facilitate the migration of datasets into the Aunsight high performance, SQL-compliant storage infrastructure. Datamart configuration settings allow engineers to specify transformations to apply to the source datasets during migrating into the storage engine, and how that data should be presented to the user in the Daybreak web app. As a result, Datamarts provide a management surface to streamline the creation and deployment of Daybreak datamarts every time a datamart is refreshed.

Users whose Daybreak implementations make use of Datamarts may immediately notice significant improvements in query performance as their data now resides within our high-performance SQL-compliant storage engine. Less immediately noticeable but equally important, enhanced capabilities with data migration will occasion fewer interruptions in the nightly pipeline jobs that refresh Daybreak datamarts. It should be noted that existing clients will not be able to take advantage of these features until Datamarts are implemented as a part of their solution pipeline.


Pipelines are new Aunsight automation components for managing the delivery of client solutions. Similar to workflows, pipelines define a sequence of workloads that should be run in order to process data for a client solution, but unlike workflows which are often created to orchestrate small processes that form part of the overall production solution, a pipeline defines the complete, end-to-end process and provides mechanisms to manage failures in the stages used to deliver finished datasets to clients via a solution like Daybreak.

Pipeline objects allow solution engineers to define the stages of a production solution and manage related components that comprise those stages, such as Workflows and AuQL scripts. Pipelines also streamline the parameterization of component stages by passing certain metadata such as storage and compute resources to use onto the dependent stages of a pipeline. Finally, Pipelines enable more resilient management of production workloads through retry mechanisms that can ensure a client solution can still be delivered on schedule even if one component experiences a job failure.

Release Contents

Issue ID Title
AUN-14610 Datamarts: Add permissions to policies and standard roles
AUN-14580 Add new "log" category of operations to lib-pig
AUN-14573 add kill button to datamarts job page
AUN-14556 Daybreak: Add row count to data results
AUN-14541 Remove references to 'rowDelimiter' in atlas records
AUN-14540 Add metadata field in the UI to show started_at field for datalab
AUN-14539 Model service: Disable deletion for published model versions
AUN-14526 Daybreak: Rename headline and button label on NLP landing page
AUN-14485 Edit atlas record directly from UI
AUN-14400 Daybreak: Add tooltips table fields in SQL editor
AUN-14379 Daybreak: Add one-to-many to query wizard
AUN-14213 DSV output format
AUN-14028 Rename cancel to close in expression builder
AUN-14027 Improve validation in expression builder
AUN-14639 Add index(s) to prevent error when paging through long Dataflow lists
AUN-13908 memento series dependency timestamp mode
AUN-14367 Add AuQL job kill method and command to lib-au-js and toolbelt
DATAINT-480 AU TXWF Date format standardization (8601)
DATAINT-38 Aon Mongo Accessibility
PZ-387 Improve Warehouse Workflow to better handle failure

Bug Fixes

Issue ID Description
AUN-14708 Bug in relation column showing in wizard
AUN-14699 Fixing the dataflow builder bug for not adding extra input fields for certain operations
AUN-14681 Datamart relax table compatibility checking
AUN-14659 Daybreak - Insights -numeric aggregators are listed on non-numeric fields
AUN-14642 The ingest tab of Datasets is blank in the mar21 release candidate
AUN-14641 Daybreak-Insights: Remove Insights from all SQL views
AUN-14578 Custom pipeline job names get overwritten with pipeline name during pipeline execution
AUN-14548 Workflow stats not loading
AUN-14564 Daybreak: Fix issue with query list open/close icons
AUN-14497 Moment dependency is taking up significant space in lib ui
AUN-14432 The SQL Read Connector allows spaces with field names, Aunsight doesn't, need schema creator to address that.
AUN-14386 Check-context-permissions throws error when checking only global perms
AUN-14337 Daybreak-Page doesn't scroll when page has a lot of content
AUN-14329 Deleting a memento series with the same key twice throws an error
AUN-14328 Update Storybook version and fix modal bug
AUN-13962 Query Workflow component has small bug in the failure return.
AUN-4116 Injecting pig code is possible via dataflow builder
AUN-14637 Fix sonar issues
DATAINT-456 Naveego Agent leaving rogue plugin processes running