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Banks and financial institutions gather data from multiple sources in various formats. This data is essential to customize product offerings, enhance customer service, and ensure complete account management. But, to unlock the value of these insights from cloud data warehouse, organizations rely on ETL tools to ingest large volumes of data. These tools are often expensive and take a lot of time for data ingestion.
What if there was a faster, easier, and more cost-effective way to ingest and orchestrate data to your data warehouse?
Virtusa’s Automated Data Ingestion is a cost-effective way for banks and financial institutions to cut down on the time it takes to ingest large volumes of data from disparate sources and formats from months to days or weeks.
Our framework drives automated metadata-based ingestion by creating centralized metadata sources, targets, and mappings. Through electronic intake and data pipeline orchestration, banks and financial services institutions can:
- Reduce costs by scaling back or eliminating ETL tools for data ingestion
- Decrease the reliance on architect teams for data pipeline development and analytics
- Ingest and organize data at an accelerated pace
- Validate and monitor data in production
- Enhance data visualizations
Key features
We support a wide-range of ingestion formats, sources, and mechanisms, with in-house knowledge to integrate with cloud-based modern tools. With the ability to use python and open-source tools, our framework accelerates ETL processes and adds transparency.
Features include:
- Schema discovery from file, database, or API-based sources
- Source and target data profiling
- Flexible data comparison between source and target datasets
- Interactive metadata setup, viewing, and usage for other purposes, including data governance and access policies
- Ingestion task setup
- Data mappings, validations, transformations, and quality check setup
- Data pipeline orchestration
- User interface (UI) to setup and manage metadata in the target table (Snowflake, Redshift, or similar)
- Dashboard to view ingestion status and exceptions
- Metadata-driven, low/no-code ingestion to handle simple to medium-complexity transformations through metadata definition or parameterization
- Hooks for security-related integration, including authentication and authorization mechanism in the enterprise
Virtusa’s Automated Data Ingestion is flexible and easily customizable to suit your needs. It can be used as a solution or a blueprint accelerator code and expedites product delivery while enhancing data visualizations. It also allows for minimal vendor tie-in because it uses python and integrates high, in-demand open-source libraries.