Our data quality solution allows you to manage the entire data quality life cycle and we know data quality improvement is not done once but a process. At every phase, the solution will ensure easy profiling and identification of data quality problems, ability to preview data, promote collaboration and configure repeating processes to ensure and maintain a high level of data quality.
- Data cleansing: Correct nonstandard or duplicate records as well as unknown data types.
- Business glossary & lineage: Ability to align business and IT, relate business and technical metadata, and visualize how changes affect other data assets.
- Data integration: Automate data quality processes into Extract, Transform and Load (ETL) and extract, load and transform (ELT) activities from multiple sources.
- Entity resolution: Identify individuals across multiple data sources from incomplete relationships.
- Foundational master data management: Achieve a single view across multiple sources for one domain.
- In-database technologies: Can shorten the time needed for key data quality and analytical processes by carrying out data quality and scoring functions in the database.
- Visualization & reporting: Create reports and share information about data management initiatives as well as monitor data health and status of remediation issues.
- Data remediation: Allows routing data issues to the right data steward or DBA for resolution.
- Unified web-based console: Monitor data quality jobs, and view data issues and governance activities.