Precisely Data Integrity Suite - Data Governance

Precisely Data Integrity Suite Data Governance offers a unified environment to centrally manage all policies, roles, and processes associated with data governance. Its modular design enables the implementation of standardized workflows ranging from metadata cataloging to defining access policies, ensuring the integrity and confidentiality of information throughout its entire lifecycle.

The automatic classification component analyzes attributes such as content, context, and sensitivity of each field to generate labels based on internal rules or regulations (GDPR, CCPA). In addition, data lineage visually documents transformations and record paths, making audits and impact analysis easier in the event of schema or ETL process changes. These capabilities integrate with a policy approval system that orchestrates staged reviews and authorizations before publishing new datasets or modifying existing definitions.

To ensure a holistic view, the platform includes real-time dashboards with compliance metrics, roles, and quality scores, as well as configurable alerts for non-compliance or unauthorized access. Thanks to its native connectors and REST API, it can easily integrate with data warehouses, BI tools, and ETL pipelines, ensuring all applications consume governed data under a unified security and quality framework.

What key features does Precisely Data Integrity Suite Data Governance offer?

• No-code configuration of policies, processes, and roles.

• Automated metadata capture from source systems.

• Semantic classification and artificial intelligence for labeling.

• End-to-end data lineage documentation.

• Interactive dashboards with quality and compliance metrics.

Feature Details

1. Flexible policy and process configuration

The service offers a configurable metamodel that allows for agile definition of policies, processes, and roles required for data governance. Thanks to its no-code approach, business stakeholders can easily adapt usage rules, approval cycles, and compliance criteria without relying on development teams, speeding up adoption and ensuring documentation consistency across the organization.

2. Automated metadata capture

Through technical harvesting techniques, the module continuously and automatically extracts metadata from source systems, including schemas, tables, views, and field definitions. This process removes much of the manual inventory work, ensures an always up-to-date view of assets, and lays the foundation for later classification and lineage layers.

3. Semantic classification and artificial intelligence

It incorporates AI/ML algorithms for auto-populating descriptions, semantic classification of columns, and assignment of thematic tags to assets. These capabilities enrich the catalog with implicit relationships and reveal business connections, improving consistency and reducing human error in documentation.

4. Natural language search and discoverability

The natural language search feature allows any user, technical or business, to find assets simply by entering queries in their own language. It supports synonyms, semantic tag filters, and contextual results, boosting team autonomy and reducing dependence on IT staff.

5. Lineage and dependency documentation

Each data asset is automatically linked to its ancestors and descendants within flows, reports, or ETL processes, generating a detailed lineage map. This end-to-end traceability provides transparency about origin, transformations, and impact of each data point, essential for audits and risk analysis.

6. Responsibility assignment and workflows

The module allows assigning each asset to a data steward, business owner, or another governance role, defining SLAs, notifications, and customized approval workflows. This establishes a clear responsibility framework and automates escalations in case of deviations from established policies.

7. Governance dashboards and scoring

It provides interactive dashboards displaying KPIs such as the data governance score, policy compliance rates, and remediation times. These metrics offer an executive view of governance status, helping prioritize continuous improvement initiatives and validate results during audits.

8. Native integration and extensibility

It integrates seamlessly with the suite’s central catalog and with external BI solutions, data lakes, or data mesh architectures. Its API-based design simplifies adding new sources and extending workflows, ensuring evolution alongside the corporate data ecosystem.

Technical Feature Overview

Precisely Data Integrity Suite Data Governance provides a unified environment to centrally orchestrate all policies, roles, and processes related to data governance. Its modular approach supports gradual adoption of key capabilities, from metadata cataloging and data lineage tracking to access policy definition and quality control at every stage of the information lifecycle.

In the metadata cataloging module, the platform performs an automatic scan of sources (databases, data lakes, ETL systems) to index schemas, tables, columns, and business attributes such as owners and SLAs. This ensures a holistic view of assets, reduces duplication of effort, and speeds up identification of relevant resources.

Automatic classification uses machine learning techniques and predefined rules to assign sensitivity labels (personal, financial, critical data) according to internal standards or regulations (GDPR, CCPA). Results can be fine-tuned through custom rules so each field is properly marked and its access regulated by confidentiality level.

The data lineage component generates interactive graphs tracing the path of information from its origin (OLTP systems, ETL processes) to end consumers (dashboards, APIs). This end-to-end visualization quickly reveals failure points, helps assess impact of changes, and ensures compliance with internal or regulatory audits.

For policy and role management, the internal engine authorizes read, write, and approval actions at project, folder, or entity level. The workflow includes staged approvals, with automatic notifications and detailed logs of each request and its resolution, optimizing collaboration between data and compliance teams.

Integrated dashboards display real-time compliance indicators, quality scores, and alerts for deviations or unauthorized access. In addition, historical reports enable trend and comparative analysis, providing insights to adjust policies and continuously improve data reliability.

Precisely Data Integrity Suite Data Governance maintains native connectivity with data warehouses (Snowflake, Redshift, Azure Synapse), BI platforms (Power BI, Tableau), and ETL pipelines through its specialized connectors. Its RESTful API supports automation of critical tasks, such as metadata synchronization or scheduled quality checks.

Finally, version control records every modification to definitions, policies, and labels, allowing rollback to previous states and comparison of differences between versions. The audit log documents who, when, and how each action was taken, ensuring full traceability that reinforces governance and regulatory compliance.

Strengths and Weaknesses Table

Licensing and Installation

Regarding licensing, Precisely Data Integrity Suite Data Governance is offered through flexible subscription by user or data volume managed, including freemium trial options and enterprise agreements with advanced support. In terms of company size, the platform scales from SMBs and small teams to large enterprises, adapting features and service levels according to the size and complexity of the data environment.

As for the installation type, it runs exclusively as a cloud SaaS solution, ensuring rapid deployment, centralized maintenance, and high availability without the need for on-prem infrastructure.

References

Official page of Precisely Data Integrity Suite: Data Governance Service of the Precisely Data Integrity Suite