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Simplified governance and building trust in data putting consistency and standardization at the forefront across teams.
Automatically identify and classify sensitive data and PII using customizable, predefined policies, or categorize assets manually in the catalog, so governance and control over critical information stays consistent across your stack.
Our advanced Governance module automates the management and protection of your most valuable data assets, ensuring robust security, regulatory compliance, and data privacy. With intelligent classification and tagging, your organization can streamline governance processes and stay ahead of evolving compliance requirements.
Automate the management and protection of your most valuable data assets with intelligent classification and tagging, so your team keeps up with evolving compliance requirements without manual governance work.
All changes and requests within these modules are subject to an intuitive approval workflow, ensuring full oversight and control before implementation. This process safeguards your data governance policies, promoting accountability and minimizing the risk of unauthorized modifications.
Assign stewards and owners to data assets and terms, and route every change and access request through an approval workflow, so accountability is clear and no critical data element goes unowned.
Decube’s workspace enforces robust access controls by assigning user permissions to specific groups, ensuring only authorized personnel can access sensitive data. This granular approach to asset management safeguards your data, promoting both security and compliance across your organization
Implement precise access controls that allow you to restrict user access to specific data assets, rather than broad access to the entire source. This granular approach enhances data security, ensuring that users only interact with the information they are authorized to handle.
Assign role-based permissions and restrict access to specific data assets and fields, not just whole sources, so only authorized people can see sensitive data and every access change is controlled and auditable.
Classify, control, and prove trust in your data, all from one governance tool.
Automatically tag sensitive and personal data across your entire stack.
Control who can see and use each dataset with role-based access.
Define and enforce governance policies consistently from one place.
Assign an owner and steward to every critical data asset.
Trace how sensitive data flows, column by column, across systems.
See who accessed what and when, and prove it to auditors.
Connect your sources and Decube auto-catalogs your assets and classifies sensitive and personal data.
Assign stewards and owners, define who can access what, and enforce policies across the stack.
Track access and changes, and produce audit-ready evidence for regulators on demand.
Give models the governed, trusted context they need, and control who and what can access sensitive data.
Feed models governed metadata, definitions, and lineage so answers stay grounded in trusted data.
Apply the same classification and access policies to AI as you do to analytics.
Know which data is documented, owned, and safe to use for AI initiatives.
and many more...
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Safeguarding your information with industry-leading standards.
Ensuring your information is protected with the highest level of integrity.
Ensuring the confidentiality and integrity of your healthcare data.
Protecting personal data with robust privacy and security measures.
Your data is encrypted in motion with TLS and at rest with AES-256.
If any of these sound familiar, your data needs governance you can prove.
No one is sure who owns critical data or who can access it.
Audits and regulator requests take weeks of manual evidence gathering.
You cannot prove who accessed sensitive data, or why.
Sensitive and PII data is not classified or tracked.
Different teams define and access the same data inconsistently.
You are rolling out AI on data no one has governed.
Built for regulated teams accountable for sensitive data, where a governance gap turns into a compliance problem.
Classify, control, and prove how sensitive financial data is used, from source to report.
Automated PII and sensitive data classification
Field level access control and RBAC
Critical data elements mapped for BCBS 239
Column level lineage for audit evidence
Keep policyholder, claims, and payment data governed and audit ready.
Policy based classification of regulated data
Role based access to claims and payment records
Stewardship and ownership on every critical asset
GDPR and HIPAA policy enforcement
Govern subscriber, network, and billing data under strict regulatory oversight.
Automated classification of subscriber and PII data
Role based access across network and billing systems
Ownership and stewardship for critical data elements
Column level lineage for audit and compliance
Give every team one consistent policy layer to classify, control, and prove data use.
Automated classification across every source
Field level access control and approval workflows
Clear ownership for critical data elements
GDPR, HIPAA, and BCBS 239 policy enforcement
Trusted by organizations operating under OJK, BNM, MAS, and APRA regulatory frameworks across APAC.
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Rated 4.6/5 on
Automation of Monitors
Data Lineage
Their data contract module is amazing which virtualises and runs monitors.
Big fan of their UI/UX, it simple but managing all the complex task.
My team uses on a daily basis.
Seamless integration with all the data connectors. We also liked the new dbt-core connector directly integrated with Object storage.
Automated Column-Level lineage
Perfect blend of Data Catalog and Data Observability modules.
Business users are able to understand if the reports /dashboard have issues / incidents.
Personally liked the monitors by segment since we have mulitple business it provides incidents breakdown by attributes.
UX and UI, features, flexibility and excellent customer service. People like Manoj Matharu took the time to understand my business and data needs before trying to solution.
One of the best-designed data products. Our complete data infra is getting observed and governed by decube. My fav is the lineage feature which showcases the complete data flow across the components.
What I appreciate most about Decube is its intuitive design and the way it supports maintaining data trust. The platform allows for straightforward monitoring of data quality, making it easier to detect issues early on.One of the most valuable aspects is the transparency it brings to our data pipelines, which also streamlines collaboration among teams. The greatest benefit is the assurance that our data remains accurate, consistent, and prepared for decision-making, all without the need to spend countless hours troubleshooting.
Decube is packaged of solution for us. We were struggling to find one good tool in which we can intigrated with our existing data stack we are using mysql. As a DevOps we used to write crond jobs to check data quality but when we adapt this tool the work and quality both are improved. I highly recommend !
Data governance is the practice of managing data availability, usability, integrity, and security across an organization. It ensures that data is trustworthy and consistent so that business decisions and AI initiatives are based on reliable information.
A strong data governance framework typically includes data ownership, data quality management, metadata management, data lineage, business glossary, and access control. Together, these components create a foundation of trust in enterprise data.
AI systems are only as good as the data they consume. Data governance ensures data is accurate, consistent, and contextualized—helping organizations achieve higher ROI from AI and reducing the risk of biased or incorrect outputs.
Common challenges include siloed data systems, lack of clear data ownership, inconsistent policies, and resistance from business teams. Modern platforms help simplify governance by automating metadata capture, lineage, and quality checks.
Data management focuses on the technical handling of data (storage, integration, processing), while data governance defines the rules, roles, and policies that guide how data should be used responsibly and effectively.
Data governance involves collaboration between multiple stakeholders: data stewards, data engineers, business analysts, compliance officers, and executives. Increasingly, organizations are forming Data Governance Councils to drive accountability.
Modern data governance tools unify cataloging, lineage tracking, observability, and business glossaries in one platform. Decube does this on a metadata-only architecture, so classification, access control, stewardship, and column-level lineage all work against one connected view of your data.
Both. Decube is a unified data trust platform, so governance runs on the same foundation as its catalog, lineage, and observability. Classification, access, stewardship, and compliance all work against one connected view of your data.
No. Decube uses a metadata-only, query-pushdown architecture, so your data never leaves your environment. This is why regulated banks trust Decube for governance.
Yes. Banks and regulated enterprises use Decube to define critical data elements, enforce GDPR/HIPAA/BCBS 239-style policies, and prove data derivation with column-level lineage.
Book a 30-min demo with us and see how lineage, quality, governance, and compliance come together in a single platform.
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