Platform

New Features

1. Enhanced Data Sheet with MySQL 8.0 support.
2. Strengthened MongoDB with SSL support.
3. Admin Module: Streamlined validation option for the following key Admin Settings:
1. Data Sheet Settings
2. Data Catalog Settings
3. Form Settings
4. Clear Confirmation for Deletion: The Delete confirmation dialog box now displays the specific item name, ensuring users confidently delete intended items.
5. Data Center: Users can access detailed information about selected Data Store Meta Data conveniently through the newly added info drawer for the Data Store Meta Data.

Please Note: The BDB Platform is compliant with OWASP security standards.

Data Preparation

New Features

1. Data Set Filter Functionality: We have introduced a powerful filter functionality for data sets that enable users to easily refine and focus their data analysis based on specific criteria.
2. Expanded Data Types:
1. Gender: To accurately represent and analyze gender-related information within our data sets.
2. Email: To handle and analyze email addresses more effectively. This enhancement improves data validation, allows for email-specific transformations, and enhances our ability to analyze email-related patterns and trends.
3. URL: To gain valuable insights from web-related data and optimize web-centric analytics.
4. Boolean: It represents binary data with values of true or false. This inclusion enables streamlined handling of Boolean data, facilitating logical operations, filtering, and accurate representation of Boolean values within our data analysis.
3. We have added the following new data transforms to enhance data quality:
1. Columns
1. Ends with
2. Random Number Between Zero and One
3. Remove Trail and Lead Quotes
4. Remove Trail and Lead Whitespace
5. Remove Whitespace
6. Split Email
7. Split HTTP Query String
8. Split URL
9. Starts with
2. Dates
1. Convert From UTC
2. Convert Timezone
3. Convert To UTC
3. Functions
1. Base64 Decode
2. Base64 Encode
3. Ceiling Columns
4. Copy Column
5. Count Distinct
6. Degree To Radians
7. Get URL Parameters
8. If NULL
9. If Then Else
10. IN
11. Is Mismatched
12. Is Missing
13. Is NULL
14. Is Valid
15. Log of Column
16. Nest Column To Object/Array
17. PI
18. Power of Column
19. Radians To Degree
20. Round values for Columns
21. Sign of Columns
22. Sqrt of Column
23. Trigonometric Functions
4. Integer: Provided with the Modulus operator in this transformation.
5. String
1. Add Prefix
2. Add Suffix
3. Convert Values to Column
4. Get Domain
5. Get Host
6. Get Subdomain Name
7. Is Even
8. Is Odd
9. Negate Boolean Value
10. Remove Accents

Data Pipeline

New Features

1. Jobs:
1. Job Migration: We have introduced the capability to migrate jobs, enabling seamless transfer and deployment of job configurations across environments. This enhancement streamlines the process of moving jobs between different systems, facilitating efficient job management and ensuring consistency in job execution.
2. Share Option for Jobs: We have added a Share option for jobs, allowing users to easily share Jobs with relevant stakeholders. This feature promotes collaboration and knowledge sharing, enabling team members to leverage and replicate successful Jobs.
2. Kafka Partition and Data Size: We now provide improved monitoring and control over Kafka partitions and data size. This enhancement allows users to effectively manage their Kafka infrastructure and make informed decisions for scaling and optimization.
3. Component-Level Failure Alert: We have introduced a component-level failure alert mechanism, providing notifications as alert flags on component failures. This can be seen on the pipeline list and within the pipeline workflows. These alerts can be ignored by the data pipeline developer based on the actions taken. This helps in minimizing disruptions and ensuring the smooth operation of the Pipeline.
4. Introduction of Synthetic Data Generator Component: The new Synthetic Data Generator component equips users with advanced data generation capabilities, enabling them to effortlessly create synthetic data. This Component generates synthetic data based on the given schema (Draft-07)/ sample data (JSON, CSV, Excel).

1. List Pipeline Page:
1. UI Failure alerts are now visible on the List pipeline page. The Page brings in several pipeline-level information that brings better monitoring just by going to the list.
2. User-Friendly Filters have been introduced on the page along with the resource configuration button.
3. Click on the pipeline name to view the details of the pipeline. Once clicked, a drop-down window will open displaying the details of the pipeline and failure and ignored components in the pipeline.
2. List Jobs Page: Click on the job name to view the details of the job. Once clicked, a drop-down window will open displaying the details of the job and run history.
3. UI/UX enhancements: Improved UI design has been provided for the failover navigation specifically regarding component failure alerts for ease of access.

Data Science Lab

New Features

1. Faster Model Explainer: This optimization ensures that users can obtain valuable insights and interpretability from their models with greater speed and accuracy, facilitating informed decision-making and boosting the overall effectiveness of the analytics process.
2. Enhanced Auto ML Model Creation: We have introduced validation functionality within the Create Experiment process of our Auto ML feature. This enhancement allows users to validate and verify the selected algorithm types/ prediction model before initiating the model training process.
3. Streamlined Model Explainer Dashboard: We have enhanced the usability of the Model Explainer Dashboard by introducing support for a new load function within it. This addition enables users to easily load and analyze model explanations and gain deeper insights into the factors influencing predictions.

Enhancements

1. UI Enhancements in the Explainer Dashboard
1. Restricted the maximum number of features up to 15.
2. Added a search bar to feature the input table in the What If Analysis tab.
3. Provided pagination to feature input table in the What If Analysis tab with a minimum of 8 features.
4. Added selected range in the Select Index plot.

Designer

Enhancements

1. Service Update: We have implemented a service update that enhances the efficiency and reliability of our system. We have transitioned from WSDL to utilizing the more advanced “getendpointurl” approach.
2. Single Value Component Tooltip Fix: We have addressed a fix related to the tooltip functionality in our Single Value component. This fix ensures an accurate and consistent display of tooltips.

Story

New Features

1. PostgreSQL Data Store Settings: We have enhanced the Data Store Settings for PostgreSQL by introducing support for adding synonyms. This allows users to define and manage synonyms within their PostgreSQL Data Store for more efficient navigation and querying of data.
2. Category Color Support: We have introduced support for category color in our visualizations. This enhancement enables users to assign specific colors to different categories within their data, facilitating easier identification and differentiation of data points or groups.
3. Conditional Color Support: We now offer support for conditional color formatting in our Story module. This feature allows users to define conditional rules based on specific criteria or thresholds and apply different colors to visualize variations or anomalies in their data.
4. Customized Slice Color Support: We have introduced the ability to customize slice colors in our Stories. This functionality empowers users to assign specific colors to individual slices, providing greater control over the visual representation of data.
5. Data Grid chart:
1. PDF Export in Tabular Format: The PDF export option for the Data Grid chart now exports the chart data in a tabular format. This enhancement allows users to easily export and share their Data Grid chart data in a PDF file.
2. Field Re-Ordering Support: We now support the re-ordering of fields in the Data Grid chart. By allowing field re-ordering, users can present their data in a more logical and meaningful way, improving the overall clarity and usability of the Data Grid chart.