By Fivetran
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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.
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.
Real-Time Analytics
Track data and system backups, replication, and failover events.
Solution Integration
Integrate with other management, resilience, or backup solutions
Infrastructure Compatibility
Be compatible with a variety of cloud and/or virtual infrastructure.
Monitoring
Monitor replication environment via GUI
System Failover
Provide as-before failover capabilities for cloud environments.
Pay by Usage
Services are offered under a pay-as-you-go or utilization-based purchase model.
Service Provision
Offer disaster recovery capabilities as a third-party provider.