About Data Mapping
Data Mapping is a software platform from Privado AI that supports the visualization and organization of data structures. It combines data lineage tracking, schema mapping, and change rules so users can effectively manage data flows and ensure compliance with regulations. This platform is designed to help organizations understand relationships between datasets, enabling better decision-making and risk management. Specifically, Data Mapping facilitates integration with various data sources and offers intuitive mapping interfaces for users. Key capabilities: data lineage visualization schema enforcement impact analysis change tracking integration with data catalog tools Best for: data analysts and compliance officers that need to map and manage complex data relationships.
Data Mapping by Privado.ai is a dynamic privacy management solution designed to give organizations complete visibility into how personal data flows across their systems and applications. The user interface of Data Mapping is built with clarity and accessibility in mind. Its dashboard presents real-time visual maps of data flows, making it easy for privacy teams and developers to understand complex structures at a glance. The interface is highly intuitive, with interactive elements that allow users to drill down into specific applications, datasets, or APIs. This visual-first approach is a unique design element that sets it apart from traditional compliance tools, which often rely on static text-based records. Navigation is streamlined, ensuring that even users without deep technical expertise can quickly identify sensitive data usage and potential risks. Functionality is where Data Mapping excels. The software automatically scans codebases, APIs, and applications to generate dynamic maps of data movement, reducing the manual effort required for compliance documentation. It offers features such as risk detection, automated compliance reporting, and integration into developer workflows, enabling privacy checks directly within the software development lifecycle.
Pros & Cons
- +Automated scanning of codebases and APIs eliminates the need for manual questionnaires.
- +Real-time dynamic maps give visibility into sensitive data flows across applications.
- +AI agents fill blind spots in data mapping, reducing compliance gaps.
- +Auto-categorization of personal data (health, financial, location) improves accuracy in risk detection.
- +Continuous monitoring ensures maps stay updated as systems evolve.
- −Initial configuration can be complex for organizations with fragmented data environments.
- −Documentation lacks depth, requiring trial-and-error for advanced features.
- −Customer support response times vary depending on subscription tier.
Features
Key features
- Automated data mapping
- builds complete maps without questionnaires
- Code scanning
- maps data and risks from first‑party apps and backend code
- Web and app scanning
- tracks collection/sharing across websites and mobile apps
- Third‑party scanning
- identifies all recipients and alerts on new sharing
- AI‑assisted RoPA
- completes registers using real‑time scans and documentation
- Cross‑tool syncing
- syncs data maps to OneTrust and TrustArc
Additional features
- Personal data inventory
- auto‑categorizes and tags sensitive data
- Real‑time alerts
- flags new data elements, third parties, and cross‑border sharing
- AI agents
- fill gaps and eliminate manual assessments
- Privacy evidence records
- auto‑document collection, use, storage, sharing
- Resources
- ebook, webinars, and product privacy guide
Pricing
Monthly plans
Enterprise
AUD 250
Countries & Languages
Interface languages
Billing currencies
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About Data Mapping
Data Mapping is a software platform from Privado AI that supports the visualization and organization of data structures. It combines data lineage tracking, schema mapping, and change rules so users can effectively manage data flows and ensure compliance with regulations. This platform is designed to help organizations understand relationships between datasets, enabling better decision-making and risk management. Specifically, Data Mapping facilitates integration with various data sources and offers intuitive mapping interfaces for users. Key capabilities: data lineage visualization schema enforcement impact analysis change tracking integration with data catalog tools Best for: data analysts and compliance officers that need to map and manage complex data relationships.
Data Mapping Details
Data Mapping's In-App Market Place
Does Data Mapping have an in-app market place?
Yes
How many Mini-Apps in the marketplace?
1
Mini Apps
NA
Pricing Options
Plans
Monthly plans
Enterprise
AUD 250
Accepted Payment Currencies
USD ($)
Pros & Cons
- Automated scanning of codebases and APIs eliminates the need for manual questionnaires.
- Real-time dynamic maps give visibility into sensitive data flows across applications.
- AI agents fill blind spots in data mapping, reducing compliance gaps.
- Auto-categorization of personal data (health, financial, location) improves accuracy in risk detection.
- Continuous monitoring ensures maps stay updated as systems evolve.
- Initial configuration can be complex for organizations with fragmented data environments.
- Documentation lacks depth, requiring trial-and-error for advanced features.
- Customer support response times vary depending on subscription tier.
Data Mapping's Support Options
Email Address
support@privado.aiDocumentation
https://help.privado.ai/enData Mapping's Alternatives
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