DQC Platform
Stop letting wrong data hurt your business
Shift from manual checks and isolated cleanups to proactively taking control of your master and transactional data. DQC AI gives you a sustainable solution to automatically check and improve your data, with humans-in-control.
Using the DQC Platform
Effectively find and improve wrong master and transactional data. Combine AI with human intelligence and control for full transparency.
Built on 3 pillars
DQC Platform for 100% fit-for-purpose data
1) Find data issues with AI.
- Set up data quality rules with the help of DQC AI agents
- Import any rules, requirements, or issue descriptions in natural language or as code in seconds
- Find issues in the data and let the AI agent document everything for you
2) Improve data at source with AI + human experts.
- Generate AI suggestions for data improvements
- Fix issues at source with subject matter experts in full control
- Track the change history for complete visibility
- Observe data quality improve over time
3) Prevent issues at source.
- Use all data quality rules on the DQC Platform via API or SDKs
- Embed the DQC data quality rules directly in your core systems
- Prevent data issues in real-time in source systems Stop bad data from flowing through your data pipelines / ETL processes
How the DQC Platform leverages AI
Artificial intelligence sits at the core of the DQC Platform
The proprietary DQC machine learning engine automatically generates smart data quality rules by analyzing your data patterns, saving weeks of manual rule creation. This AI-driven approach identifies complex relationships across datasets that would be difficult and time-consumting to spot manually. The DQC Platform also leverages large language models specifically for contextual data understanding, enabling the suggestion of meaningful rules, and improvements for problematic data by drawing from both internal knowledge and external sources. For example, the system can automatically validate addresses, standardize product descriptions, or identify misclassified items without human intervention.
Integrations
Examples
Companies can generate value by improving their data
Dealing with data quality issues at the source lets businesses start with a strong foundation and make the most of GenAI, DQC’s Dr. Michael Spira explains.
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Start treating data as an asset, today. Learn how AI agents can help you improve your company data.