Data has become one of the most valuable assets for enterprises today. However, managing and governing data remains a key challenge. With data coming from disparate sources and stored across siloed systems, many companies struggle with data sprawl.
This makes it difficult to ensure data security, privacy, quality and regulatory compliance. Without the right data governance strategy and solutions, organizations run major risks of data breaches, inaccurate analytics, poor decision making and non-compliance penalties.
In this comprehensive guide, we discuss the significance of data governance, provide an overview of leading software solutions and offer best practices for implementation.
Why Data Governance Matters
Data governance refers to the overall strategy and policies for managing enterprise data. It establishes roles, processes, guidelines and technologies to ensure data is:
- Available and easily accessible to authorized users
- Accurate and reliable for business insights and reporting
- Protected and secure from unauthorized access or leakage
- Compliant with regulations around data privacy, financial reporting etc.
Without governance, companies lose control over their data assets. This leads to inability to trust data for decisions, higher risk, lowered productivity and non-compliance fines.
As per a Ponemon Institute survey, inadequate data governance costs organizations an average of $12.9 million per year.
Hence implementing data governance is no longer an option but a strategic priority for digitally-driven companies.
Core Capabilities of Data Governance Software
Data governance solutions offer a centralized platform to establish and enforce data policies across the organization. Here are some of the key capabilities:
Data Catalog
A data catalog serves as an inventory of data assets. It documents critical metadata like data owners, definitions, lineage, quality metrics etc. This aids discovery and enables trust in data.
Metadata Management
Centralized management of metadata provides context around data assets. This is key for collaboration, reporting and compliance.
Data Lineage
Data lineage provides visibility into the flow of data from sources downstream to other systems, models and reports. This is crucial for maintaining quality.
Policy Enforcement
Platforms provide capabilities to define granular policies around data access, security and use. Built-in controls restrict access to sensitive data.
Workflow Automation
Data governance involves ongoing management of policies, standards, issues etc. Automated workflow streamlines and simplifies governance processes.
Leading Data Governance Software Solutions
Here is an overview of the top enterprise-grade data governance platforms:
1. Collibra
Collibra provides an integrated platform to catalog data assets, define policies and standards and track compliance. Key features include:
- Data intelligence through cataloging, stewardship and glossaries
- In-depth lineage mapping showing upstream and downstream dependencies
- Role-based access control and security
- Workflow automation for policy and issue remediation
- 150+ out-of-the-box metrics on data quality, compliance and risk
Collibra integrates easily with data infrastructure and BI tools. With its robust capabilities, Collibra is a leader in data governance software.
2. Informatica Enterprise Data Catalog
Informatica offers a unified data governance solution that includes a machine learning-powered enterprise data catalog. Key highlights:
- Automated discovery and 360-degree views of data assets
- Business-friendly glossary, definitions and metadata
- Data lineage visualizations across systems and users
- Role-based access control and fine-grained policy enforcement
- Monitoring dashboard for data governance KPIs
As an end-to-end data management platform, Informatica integrates governance across data integration, quality, privacy and archival processes.
3. erwin Data Intelligence Suite
The erwin suite enables enterprises to secure, govern and understand data through:
- Automated metadata and context capture
- Data mapping and lineage across 150+ data sources
- Centralized policy and standards management
- KPI dashboards to track data health, compliance and consumption
- Universal connectivity via API integrations
erwin offers robust governance capabilities for structured as well as unstructured data. With pre-built connectors and accelerators, customers can maximize ROI faster.
4. Alation Data Governance
Alation leverages machine learning, collaboration and security models for next-gen data governance. Key features:
- Behavioral analysis to automatically capture reliable metadata
- Glossary and catalog for self-service data discovery
- Fine-grained access control policies based on data sensitivity
- Reviews and certifications to maintain the quality of asset information
- Hundreds of out-of-the-box data quality rule templates
Alation combines data cataloging, metadata management and governance in a modern interface. It focuses on usability and fostering a data culture.
5. Atlan Data Governance Platform
Atlan offers transparent data governance through community-driven curation and collaboration features such as:
- Crowdsourced data catalog with wiki-like descriptions
- Automated data discovery and classification
- Data protection rules tailored to regulatory standards
- ML algorithms to fingerprint sensitive data fields
- Data quality notifications and workflows
With its innovative transparent governance model, Atlan delivers quick time-to-value across data democratization, security and compliance use cases.
6. ASG Technologies: Data Intelligence
ASG Technologies offers capabilities ranging from data discovery, lineage and catalog to quality and access governance:
- Automated profiling and catalog of distributed data
- Data relationship analysis detecting lineage and impact
- Single platform for managing policies, standards and rules
- Compliance dashboard showing data ownership rights
- Visual workflow for remediating data issues
ASG also provides pre-built data governance accelerators for industries like healthcare, banking and insurance.
7. Global IDs: Spectrium Platform
Global IDs offers an AI-powered data intelligence platform covering key governance functions:
- Automated catalog of data assets using AI/ML
- Business glossary and dictionary for shared definitions
- Data lineage analyzing upstream/downstream flows
- Collaboration portal for crowdsourced stewardship
- Hundreds of out-of-the-box data quality rules
Global Data’s machine learning foundation enables rapid insights into data ecosystems. With its robust functionality, Global IDs solutions meet complex enterprise needs.
8. octeract: Ludos
Ludos fuses data cataloging, operational metadata management and governance. Key capabilities:
- Automated catalog with 360-views of technical/business metadata
- Data lineage analyzing complex multi-hop flows
- Data issue tracking with conversation streams
- Customizable workflows for policy and standards
- Simplified measuring and monitoring of governance KPIs
With an emphasis on usability and automation, Ludos accelerates adoption across business users and stewardship teams.
9. Infogix Data3Sixty Suite
Infogix offers a modular suite covering catalog, governance, privacy and quality functions:
- Data discovery, cataloging and classification
- Data relationship analysis and impact tracking
- Automated policy recognition with remediation
- Centralized business glossary and dictionary
- Hundreds of out-of-the-box quality/validation checks
Infogix leverages AI, machine learning and natural language processing across its portfolio. It focuses primarily on regulated industries.
10. Solidatus: Solidatus
Solidatus specializes in complex data relationship mapping through capabilities such as:
- Metadata discovery across siloed data landscapes
- Custom contextual linkage analysis
- Interactive lineage visualizations and dashboards
- Collaboration features for glossaries, definitions etc.
- Central library documenting decisions, risks and issues
Solidatus is purpose-built to navigate messy enterprise ecosystems spanning legacy systems, Cloud apps, data warehouses etc.
11. BigID: BigID
BigID offers next-gen data intelligence powering discovery, security and governance:
- AI-based discovery of personal, sensitive or critical data
- Deep analysis of user access patterns and data usage
- Contextual policy recommendations based on risk
- Ongoing monitoring of data infra for security gaps
- Hundreds of breach and compliance rule templates
BigID’s unique risk-focused approach accelerates data protection, while enabling usage. It partners well with cloud DLP tools.
12. Immuta: Immuta Automate
Immuta Automate streamlines access request and entitlement management through:
- Contextual policy recommendations based on AI
- Role management and access certification
- Real-time data usage monitoring and analysis
- Native integration with Snowflake and other warehouses
- Emphasis on enabling self-service for users
Immuta complements its strong access governance capabilities with a comprehensive data catalog and discovery solution.
Key Capabilities to Look For
When evaluating data governance platforms, buyers should assess solutions across these key dimensions:
Data discovery and catalog
– Automated vs. manual process
– Technical + business metadata
– Data classifications and glossary
– Catalog analysis and reports
Metadata management
– Lineage mapping complexity
– Impact and dependency analysis
– Metadata change triggers and alerts
– Custom metadata models
Policy and rules engine
– Fine-grained policy constructs
– Rules templates out-of-the-box
– Remediation workflows
– Access reviews and attestation
Issue collation and workflows
– Collaboration features
– Automated issue linking and clustering
– Customizable workflow templates
Reporting and analytics
– Hundreds of governance KPIs
– Dashboards and visualization
– Trend analysis for metrics
– Exportable reports
In addition, buyers should evaluate solution deployment models, scalability, interoperability, security standards and overall ease of use.
Key Considerations for Implementation
While software capabilities are crucial, realizing the full potential of data governance requires an aligned organizational strategy. Here are some leading practices:
Get executive sponsorship:
Frame data governance as a must-have strategic priority with support from CXOs. Align to value drivers like revenue upside, risk mitigation and productivity.
Foster centralized stewardship:
Establish clear ownership and accountability with roles like Chief Data Officer and data stewards responsible for governing across siloes.
Take an incremental roadmap approach:
Balance IT-led push with business-driven pull. Focus first on high-value use cases like GDPR, CCPA compliance, customer 360 etc.
Communicate polices and train end-users:
Create awareness of governance guidelines through interactive sessions. Embed training into on-boarding and role transitions.
Incentivize community-owned governance:
Motivate data creators, stewards and consumers to collaboratively sustain governance as part of their jobs.
Review metrics and share success stories:
Track KPIs aligned to data strategy covering quality, lineage, compliance, issue closure rates etc. to showcase value delivered.
Why Data Governance Should Be a Priority
With data at the heart of digital transformation, data governance has become non-negotiable. Forward-thinking companies proactively adopt governance to harness data for competitive advantage.
Leading data governance software provides the foundation to discover, manage, protect and sustain trust in data assets. While evaluating solutions, organizations should focus on usability, intelligent automation and holistic capabilities.
Combined with executive commitment, steward community ownership and usage-led iteration, data governance can transform how businesses extract value from data.
