7th Sep. 2017
Dashboard Designer
- Enhanced look, feel, and performance of the components.
- Enhancements on the dashboard responsiveness.
- Extensibility – to support the custom components.
- Introducing the Container component for easy handling.
- Users will be provided with an option to change the chart type and select X and Y axis with basic formatting at the runtime.
- Server-side pagination will be added to the Paging Grid.
- The Data Store connector will be introduced as a new data source connection in the Dashboard Designer.
Business Story
- Merge View – An option will be provided to create a view based on the two merged datastores.
- Enhancements for Datastore Scheduler and performance optimization.
- Global Filter Panel- Better management for the filtering options will be provided.
- Calculated field can be added at the view level.
- Implementing Conversational Analytics via the NLP enhancements in the text & Voice-based search.
- The ‘Analyze’ mode in the Business Story will be provided a Playable timeline.
- Introducing developer mode to design a view.
- Data store will be integrated with R & Python algorithms for advanced analytics.
- Data labels will be added to all the charts.
- Animation in chart to show data change & visual effects.
- Enhancement in Tile components.
- Introducing the ‘Export’ option in Business Story.
Predictive Analysis:
- Python Integration-Provision to write custom Python script will be provided.
- Introduction of workspace will be added.
- R -Algorithms-Refactoring will be done.
- Predictive Analysis will be introduced as a Service which can be consumed by the third-party applications.
- Introduction of the Streaming algorithms.
Geospatial Analysis:
- Addition of all the standard world shapes.
- Enhancing the Geospatial Analysis plugin for optimization.
Data Preparation:
- Introducing custom Scala components in workflows.
- Enhancing the current workflows.
- Introducing the plugin to read from multiple input source systems and write into multiple Datastore.
- Enhancement in validation functions.
- Introduction of data profiling.
- Improved error recovery.
- Enhancement in usability features.
- Output can be written into different data sources.
Data Pipeline
- Big Data Pipeline framework to be developed into a full-blown reactive big data pipeline.
- Ability to run custom Pig scripts, hive scripts, store procedures, talend job, Unix shell scripts, BDB data preparation jobs and predictive services.
- Enhanced user interface.