Product Release Notes

3.0

August 31, 2017

Platform

New Features:

  1. New Data Connectors: JIRA and Google Analytics API connectors have been added to the data connector list.
  2. The ‘Notification’ feature has been provided for pushing system notifications to users.
  3. Audit Trail: Audit log/Performance Visualization has been provided to the users.
  4. Centralized Custom Attributes have been provided to manage the bulk of users in one go.
  5. Windows AD Attribute Synchronization.
  6. The ‘Server Monitor’ module has been added to monitor server operations.
  7. Introduced new module to manage Data Sets and Data Services.
  8. A new application ‘Play’ has been introduced to increase user interactivity. Users can capture screen shots for multiple documents, annotate and create an online slide presentation both on native iOS and the web.
  9. A general workspace concept has been introduced for Dashboard Designer, Play, and Data
  10. Custom forms have been added to create and deploy custom application inside the platform.

Enhancements:

  1. Security Enhancements:
    1. Encryption is added for secured data network communication.
    2. Service side permission checks can be done for data base security.
    3. Concurrency has been improved for rapid performance.
    4. XSS HTML filter has been provided for the prevention of malicious code injection.
  2. UI enhancements for enriched look and feel of the Platform modules like Administration, Data Center, and User Management.
  3. Report plugin has been enhanced.
Note:
  1. Data Store connector is currently in Beta.
  2. The Play plugin is currently in Beta.

Business Story

New Features:

  1. Introduced NLP driven text based data search feature.
  2. Data Visualization Components
    1. Data Grid - to view multiple data values in a tabular format
    2. Map - to position data in a geographical context using different data layers

Enhancements:

  1. Improved UI for enhanced user experience.

Data Preparation

New Features:

  1. Extract: Equipped with ‘Full Load’ and ‘Incremental Load/Delta Load’ functionality.
  2. A range of components for transforming data:
    1. Add Constants of all types to input datasets
    2. Filter out rows from input Datasets by applying conditions
    3. Perform Date Transformations on date columns
    4. Perform ‘Search’ and ‘Replace’ functions on text columns.
    5. Perform Computations involving Columns and Constants.
    6. Select and Rename columns in the input dataset.
    7. Convert one type of column to another type.
    8. Perform SQL like Join operations on two input datasets.
    9. Perform SQL like union operations on two input datasets.
    10. Group by multiple columns and find Aggregates of columns.
  3. Load Features- to write the transformed data set to elastic search for visualization.
  4. Workflow Features
    1. Organize workflows into folders.
    2. Schedule workflows to run at specified intervals.
    3. Watch the status of the workflow executions.
    4. Preview the results of the workflow executions before scheduling runs.

Dashboard Designer

Charting New Features:

  1. Charts:
    1. Histogram
    2. Waterfall
    3. Decision Tree
    4. Sparkline
  2. The auto precision calculation has been added for charts.
  3. Data point labels have been added for charts.
  4. Map Chart: Addition of Australia, Canada, Asia, Europe, Middle East, Asia Pacific maps
  5. Text indicators are provided in the data grids.

Enhancements:

  1. Bubble chart- Negative values and static radius option are provided
  2. The ‘Dual’ list filter has been added.
  3. The ‘Multi Select’ list filter has been provided for the smooth interaction with the ‘Checkbox’ component.
  4. The Bar and Column chart components can display customized stack size.
  5. The Legends panel can be displayed as open by-default.
  6. The default slider range size can be set as 100%/ 50%/ 25%/ auto for the Time Series chart.
  7. An optional row has been added to display Sum/ Average / Count of column values for the Data grids.
  8. The Scorecard and pivot components can be associated with checkbox-with-legend.
  9. Multiple series are supported by the Funnel and Pyramid chart components.
  10. Strong colors (gradients) can be filled in the Heat Map chart.
  11. The scale tick marks and precision have been added for the Gauges.
  12. Repeater chart’s title can accept fixed string and value from the global variable.
  13. The auto-manipulator grouping is available up to 2 levels in the Group Bar chart.
  14. Improved merged data operation performance by adding UnderScore.js
  15. Data grids now have an option to freeze the columns and set the adjustable width to each column.
  16. Export dashboard opens a model to control all or selected components to export in pdf/ excel.

Designer New Features

  1. Usability features
    1. The properties panel can be opened by double click on the component.
    2. Component navigation is made easier by inter-switchable Property palette/ Dataset palette and Script Editor.
    3. Connection filter keys can be accessed from a drop-down menu instead of writing manually.
    4. inter-switchable configuration and script windows are provided for a connection.
  2. UI upgrades
    1. Components can be grouped together and managed by the object browser window.
    2. Operations like ‘Rename Group’, ‘Show All / Hide All Group Components’ are available.
    3. Uniform look and feel for all model boxes in the designer..
    4. The ‘Help’ section has been added in the designer and provided with more details on components/ configuration/ scripting methods and sample dashboards.
    5. The Dashboard has an option to preview dashboard without opening in edit mode.

Enhancements:

  1. A locked component in object browser can allow the users to update all properties and assign data set except positioning and dimension properties.
  2. The dashboard loading has been improved by loading configuration and property data files from the cache.
  3. The ‘Calculated fields’ can be renamed to any valid name.
  4. Timely refresh of connection is updated.
  5. An option is added to the preference page, to hide all the ‘success/ error/ warning/ information’ notifications.
  6. The ‘Summary’ can be displayed for the predictive workflows inside the dashboard.

Predictive Workbench:

New Features:

  1. Multiple workflows are now supported in R to simplify the modeling process.
  2. Components to support multiple workflows in R:
    1. Data Preparation
      • Missing Value Replacement – Missing values in a column can be replaced with a specified replacement options in data set. Replacement Options: Mean, Median, Mode, Maximum, Minimum, remove entire row, Remove entire column and Custom replacement)
      • R Split Data – Split the data set into train and test based on a ratio with sampling method like Linear sampling, Shuffled sampling, and Stratified sampling.
    2. Algorithm
      • R CNR Tree – Validation provided to R-CNR Tree to support train and test methodology.
      • R Naïve Bayes – Validation provided to R-Naïve Bayes to support train and test methodology.
    3. Validation
      • Cross Validation - Splits the data set based on the selected number of folds.
      • Bootstrap – Splits the data set based on the selected number of resampling.
      • Repeated cross validation – Repeats the split based on the selected number of folds.
      • Leave one out cross validation – Splits data based on leaving one data instance and constructs a model for all other data instances to find the best model.
    4. Apply Model
      • R Apply Model – User can connect upper part with model and lower part with test/ actual data to get prediction based on the model.
      • Save R Model – User can extract the best model from executed workflow and save.
    5. Performance
      • R performance – Users can compare up to three workflows and evaluate the performance of the models to determine the most suitable model. Users can set evaluation metrics as Binary or Multi-class.
    6. R Saved Models
      • List of saved models from where the user can use it in the workflow.
  3. The ‘Refresh’ button has been introduced to rerun the R workflow with the latest data.
  4. The ‘Clear Cache’ option is provided to clear the cached data.
  5. Components introduced in Spark Environment(Alpha release):
    1. Data Preparation
      • Spark Filter – Provides a space where users can write condition to apply the dynamic filter.
    2. Data Transformation
      • Spark PCA – Algorithm which can be used in dimensionality reduction.
      • Spark Chi Square – to select features of categorical data.
      • Spark Index to String – maps the column of label indices to back to a column containing original labels.
      • Spark SQL Transformer – provides facility to transform data based on SQL statement in spark.
      • Spark Group by – Aggregate result on basis of column.
    3. Algorithm
      • Classification
        1. Spark Decision Tree – Decision Tree with validation to introduce machine learning.
        2. Spark Random Forest – Random Forest with validation to introduce machine learning.
      • Recommendation Engine
        1. Spark ALS – Introduced ALS to provide recommendation Model.
    4. Custom Scala Script
      • The ‘Custom Scala Script’ component has been introduced to write a Scala script that can run in spark Environment. Limitation – RDD with Mllib algorithms not supported.
  6. Predictive services in Dashboard Designer – The predictive workflows can be deployed on the dashboard designer to consume it as a data source to display visualization.
  7. Elastic Search Writer in Scheduler - Workflows can now be scheduled and pushed to Business Story.
  8. Auto numbering will be displayed for the alias names of all the components of a workflow in the ‘Console’ tab while running a workflow.
  9. The predicted column name will be auto-numbered.
  10. The ‘Delta Load’ feature has been added in MYSQL to define a primary key.

Enhancements:

  1. Enhancements in Spark Components
    1. Spark R Formula – Added formula text area.
    2. Spark performance – The ‘Regression Evaluation Metrics’ has been added in Spark performance types.
  2. Suitable alignment is provided for R summary option.
  3. Icon enhancements have been done to distinguish between Spark, R, and Java components.
  4. Users can receive component specific messages to get informed about the functionalities provided by the selected component.
  5. The Scatter Matrix chart display is limited to 7*7 in K-Mean algorithms.
  6. Summary of all the components will be displayed through an email while scheduling a workflow.

Connect with BDB Expert

Connect Now