Weld Features
Functionality (18)
Diverse Extraction Points
Pull any required data from a variety of sources, including email, web pages, PDFs, and other documents.
Data Structuring
Organize extracted data into a more easily digestible structure.
Consolidation
Amass extracted data in a variety of data formats like spreadsheets and .csv.
Data Cleaning
Clean extracted data by removing duplicates, clearing excess characters, grouping by characteristic, and more.
Cloud Extraction
Stores data in cloud storage for access at any point.
Visualization
Generate visual data representations from extracted data.
Extraction
Extract data from the designated source(s) like relational databases, JSON files, and XML files.
Transformation
Cleanse and re-format extracted data to the needed target format.
Loading
Load reformatted data into target database, data warehouse, or other storage location.
Automation
Arrange ETL processes to occur automatically on needed time schedule (e.g., daily, weekly, monthly).
Scalability
Capable of scaling processing power up or down based on ETL volume.
Debugging
Ensures live debugging to alert if any failure during data sync.
Workflow Automations
Supports the creation of automated workflows and data pipelines.
Notifications
Supports notifications in messaging applications such as Slack, and even in workflows.
API Integrations
Provides several pre-built connectors and API integrations to build data workflows.
Programmed trigger of data sync
Programmatic trigger of syncs via public APIs
Incremental data sync
Native support for incremental syncing
Data audit
Move sync logs back into warehouse for auditing
Management (6)
Reporting
View ETL process data via reports and visualizations like charts and graphs.
Auditing
Record ETL historical data for auditing and potential data correction needs.
Source and Destination Selection
Allow users to select the data's source(s) and destination(s) for the exchange process.
Solution Integration
Integrate with other data-oriented solutions.
Reporting and Visualization
Generate reports, dashboards, and graphics around data exchange KPIs and stats.
Data Governance
Provide data governance strategies or capabilities for exchanged and acquired data.
Exchange Functions (2)
Data Transmission
Transmit data without altering the data’s inherent meaning.
Data Normalization
Normalize transmitted data for easier consumption by the receiving system.
Data as a Service (4)
Market Data Acquisition
Facilitate market data-as-a-service acquisition.
Industry Data Acquisition
Facilitate industry data-as-a-service acquisition.
Source Data Acquisition
Facilitate consumption source (e.g., web, mobile, IoT) data-as-a-service acquisition.
Targeted Data Acquisition
Facilitate targeted subject matter data-as-a-service acquisition.
Data Management (4)
Data Integration
Integrates data and data-related technologies into a single environment.
Metadata
Provides metadata management capabilities.
Self-service
Empowers the user via a self-service capability to manage data workflows.
Automated workflows
Completely automates end-to-end data workflows across the data integration lifecycle.
Analytics (2)
Analytics capabilities
Provides a high performance, flexibile analytics platform to support data management and embrace data driven decision making.
Dasboard visualizations
Collect and displays metrics across the data integration via a dashboard.
Monitoring and Management (2)
Data Observability
Involved solely in monitoring data pipelines, sending alerts and troubleshooting data.
Testing capabilities
Deploys testing capabilities such as report testing, big data testing, cloud data migration testing, ETL and data warehouse testing.
Cloud Deployment (2)
Hybrid cloud support
Supports analytical platforms and data pipelines across complex hybrid environments.
Cloud migration capabilities
Supports migration of component or pipeline to different cloud environments.
Data Management (5)
Data Modeling
Supports the creation of SQL models to query any data warehouse.
Auditing
Detailed logging for auditing needs.
Observability
Real-time visibility into the reverse ETL process.
Data mapping
Configures data mapping from data warehouse to target tools.
Reporting
View the reverse ETL data via reports and charts through data viz and sync progress.
Security (2)
Security Compliance
Supports industry standards (GDPR, CCPA etc) before, during, and after the reverse ETL process.
Data Encryption
Ensures data encryption across multiple levels of the reverse ETL process.
Diverse Extraction Points (1)
Diverse Extraction Points
Pull any required data from a variety of sources, including email, web pages, PDFs, and other documents.
Generative AI (3)
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
Agentic AI - DataOps Platforms (5)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Decision Making
Makes informed choices based on available data and objectives



