New Data Connector: Connect seamlessly with the
new Apache Pinot data connector.
Enhanced support for Datasheet: Datastore and
Report creation are possible now directly from the Datasheets.
Persistent Filter Values: Improved user
experience by retaining the applied filters for quicker access to Data Sets.
Admin
Migration Restrictions: Prevents migrating
Dashboards, API Services, and Pipelines within the same server and space for
enhanced control.
Resource Observability: Introduced Resource
Observability for the platform, providing enhanced visibility into resource
usage and performance.
Entitlement Implementation: Access and manage
control for shared items across the Data Center.
Enhancements
Data Center:
Datasheet List Page Updates:
Added a “Refresh Data” icon for Sandbox-based
Datasheets.
Added an Information icon to get additional
details about each datasheet.
Enhanced Execution Settings: Configure multiple
node pools for optimized performance.
File Scanning: Implemented file scanning before
uploading a file for improved platform security.
Data Store Scheduler Refresh: The default
refresh interval for the Data Store scheduler is now set to weekly, with the
refresh day aligned to the original creation day of the Data Store.
Notification Service Update: Enhanced the
notification service for improved reliability and user experience.
Strengthened security measures to protect user data
and privacy, addressing vulnerabilities found in a recent security audit.
Data Catalog Search
New Features
Columns Tab: The users get notified if a column
contains personal information.
Delete Catalog Option: Provides a Delete
icon for admin users to remove catalog entries.
Enhancements
Optimized Service Response: Enhanced response time
for faster and smoother access to the Data Catalog, providing a more efficient
experience for users.
Python Library Updates: Updated to the latest
versions for improved stability, performance, and compatibility across the Platform.
History Tab: Displays last updated details,
including recent activations and deactivations of pipeline and jobs.
Data Preparation
New Features
Introduced a new menu bar featuring transformation icons
for faster access and smoother navigation, enhancing workflow efficiency.
Copy and Paste Transforms: Users can replicate transforms and apply them to
another Data Preparation for the same data source.
Report
New Features
Report Creation: Reports can now be created based
on data stores from the Apache Pinot data connector.
Chart Annotation: Plot annotation lines on the Line
and Mixed charts to emphasize key events, enriching data storytelling and providing
greater visual clarity.
Threshold Lines: Threshold lines have been
introduced on the Line, Mixed, and Bar charts aiding in more precise data analysis.
New Charts:
Benchmark Analysis: Added a powerful Benchmark
Analysis chart for in-depth performance evaluation and comparison.
Candlestick: Introduced the Candlestick chart,
ideal for detailed financial data analysis and trend insights.
Enhancements
Optimized Report charts for accurate display in mobile
browsers.
Word Cloud Chart Enhancement: Introduced support
for displaying individual words or full sentences in the Word Cloud chart, with a
new dataset type selection option for flexible visualization.
Designer
Enhancements
Introducing Annotations: Plot annotation lines on
the Line, Mixed, and Timeseries charts to mark specific events, providing clearer
insights and contextual analysis.
Threshold Lines & Fill Color: Ensure better data
visibility to interpret and analyze data trends with the help of threshold lines and
fill color functionality in the Bar, Line, Mixed, and Timeseries charts.
Benchmark Analysis Component: Combine Boxplot and
Data Grid in one powerful visualization for a better understanding of the data
benchmarks.
Slider for Bar Chart: Effortlessly manage large
datasets by enabling the slider feature.
Entitlement Implementation: Introduced access
control for shared dashboards and workspaces.
Enhancements
Improved Date Picker: Customizable fonts, colors,
and adjustable year and month ranges for a seamless user experience.
Data Export with Formatters: Enhanced data export
functionality to include formatters for Excel and CSV, ensuring consistent and
structured data presentation.
Export to CSV: Introduced a new method for
exporting chart data to CSV through a plugin script.
Sorting Enhancement for Data Grid: Supports sorting
the date columns with the following types of date-time formats:
YYYY-MM-DD HH:MM:SS
MM/DD/YYYY HH:MM:SS
DD-MM-YYYY HH:MM:SS
ISO 8601 format (e.g., 2023-08-23T14:30:00Z)
Time formats such as 12-hour and 24-hour clocks
(HH:MM)
Please
Note:
The previous method used to export chart data to CSV has been deprecated as of this
release.
Annotation mapping is currently supported for CSV and
Excel data.
Data Science Lab
New Features
Consolidated Interface: The Export and
Register options are now combined into a single interface for streamlined
access.
Adjustable Repository Pane: Users can now adjust
the width of the repository pane for better project organization.
Registered Model and API Details: Added “Created
by” and “Parent Projects” details for each listed model or API.
Project-Level Node Pool Management: Added support for configuring multiple
node pools at the project level, enabling more efficient resource allocation and
scalability.
Feature Store Integration: Integrated the feature store as a data source for
AutoML experiments.
Notebook Markdown Control: Introduced expand and collapse functionality for
Notebook markdown cells.
Sandbox File Support for Multiple Excel Sheets: Upload Sandbox files with
multiple Excel sheets in Notebooks, improving functionality across Data Preparation,
Data Profile, Preview, and AutoML experiments, and streamlining data processing.
Entitlement Implementation: Access control for shared items across the Data
Science Lab for Projects, Notebooks, and Models.
Library Status Tracking: Get enhanced visibility over operations by tracking
library status updates for each installed library for a DSL Project.
Enhancement
Feature Store Enhancements: Added Data Preparation and scheduling
capabilities to the Feature Store, improving data management and workflow
efficiency.
Auto-Save Default: Auto-save is now enabled by default in notebooks.
Modification on Model as API: Registered Model APIs can predict the outputs
via job.
Data Pipeline
New Features
New Pipeline Components:
PySpark GCS Reader and Writer
Components: Enables reading from and writing to Google Cloud Storage
using PySpark.
BigQuery Reader Compontnt: Facilates
reading data from BigQuery.
PySpark Script Component: Allows execution
of custom PySpark scripts.
Action-based Selection Buttons: Added selection
buttons for filtering through pipeline and job lists based on actions and recent run
status for enhancing navigation and usability of Data Pipelines and Jobs.
Recent Run: Displays job status for the top 5 recent job runs on the List
Jobs page.
Filter Menu in System Pod Status Logs: Added a filter menu for better log
management.
Side Menu Bar: Introduced a Side Menu Bar on various pages, including
Pipeline Editor, monitor, and testing for improved navigation.
Expandable Graph for Pipeline Monitoring:Introduced
an expandable graph to view detailed performance metrics and trends for enhanced
monitoring and analysis.
Unique Component and Task Names: Ensure distinct names for components and
tasks (when dragging).
Pin/Unpin Functionality for Pipelines and Jobs: Users can now pin or unpin
pipelines and jobs for easier access and organization.
Recently Visited Pipelines and Jobs: The homepage displays the 10 most
recently visited pipelines and jobs providing quick access to your work.
Spark Upgrade: Upgraded Spark version to 3.5.1 for improved performance.
Java Upgrade: Upgraded Java to 17 for enhanced functionality and security.
Clear Job Logs: The Clear option helps the users clear job logs from the
Sandbox location.
A confirmation pop-up window is added for unsaved or newly configured components/
tasks to prevent accidental loss of changes.
Enhancements
Kafka Event Preview:
Improved the preview list for pipeline Kafka
events to provide more detailed and actionable information.
Kafka Preview records can be expanded from 10 to
100 records with filters for the latest, beginning, and customizable
timestamp values.
System Pod Logs: All system pod logs are available
on the System Component Status page for comprehensive monitoring and
diagnostics.
The History Panel now displays details on the
creation,
update, last activation, and last deactivation of pipelines and jobs.
The Component Version Button remains disabled when
no new
version is available for the pipeline components.
