Top 10 Data Governance Tools: Analyze Features, Pros, & Cons

In May 2023, Facebook was fined $1.3 billion by Ireland’s Data Protection Commission for breaching GDPR regulations. Even for a tech giant, it was a significant dent on its reputation and was a precedent for many more congressional hearings to follow. It was a cautionary tale for small businesses to tighten their data governance practices. 

As a business scales, their data piles up, scatters across siloed systems, and becomes increasingly difficult to manage. This is a recipe for disaster, especially if you try to manage these complexities manually. But it doesn’t have to be – especially with the advent of effective data governance tools. 

Let’s assess the best data governance tools, their key capabilities, pros, and cons.

What is data governance?

Data governance is a framework for establishing policies, processes, and standards that help ensure that the organization’s data is accurate, consistent, usable, and secure. It provides a structured approach to effectively managing data by establishing the right roles, providing guidelines on securing data, and utilizing technology to monitor and enhance data quality.

What are Data Governance tools?

Data governance tools are software systems that help IT teams manage, organize, monitor, and analyze their end-to-end data lifecycle. 

Data governance platforms define the policies and guidelines that dictate how data is classified, its movement within the ecosystem, who can access it, and the business context of a given data set. This helps organizations maintain regulatory compliance, ensure accountability, identify patterns, streamline processes, and improve the security posture. 

Data governance platforms also define the policies and guidelines that dictate how data is classified, its movement within the ecosystem, who can access it, and the business context of a given data set. These tools help with data cataloging, quality management, security, policy management and collaboration across departments.

Data governance is not an option; it is a fundamental requirement for successful data management and ensuring data quality, compliance, and security. – Girish Redekar, CEO of Sprinto and GRC expert

Best Data Governance Tools Comparison: Features, Pros, Cons

Before we present our top 10, let’s clarify a common misconception…..

There is no objective list of “best” or “top” tools for any category. This is because what works for you may not work for another company, and vice versa. In other words, it boils down to your unique business needs and goals. 

So how did we condense this list? Here are some parameters we used:

• Market reports from top tech research and software consulting companies like Gartner, G2, Capterra
• User feedback and satisfaction surveys and reviews by real users
• Common selection parameters for data governance platforms include, but are not limited to, their ability to manage regulatory standards, visualize governance components (assets, risks, controls) from a single dashboard, automate control validation, track reports in real time, and customize governance scope, just to name a few.  

Sprinto

Sprinto is a next-gen, automated GRC platform that transforms infosec compliance management and governance. It seamlessly integrates with any cloud setup without requiring additional support using powerful and responsive native integrations and APIs to produce an accurate, up-to-date inventory of security assets and infosec risks.

It ensures the highest levels of infosec governance by streamlining compliance programs, consolidating/centralizing controls and controls-related tests from each program, and tracks them as per custom defined rules/conditions.

This helps IT and governance teams gain a 360-degree view of security and compliance gaps by streamlining critical activities like vendor risk assessment, automating policy management, and continuously monitoring controls and assessing their effectiveness. 

The tool consolidates processes and workflows into a single dashboard to eliminate silos and meet end-to-end data privacy and governance requirements with little to no manual intervention. All features and capabilities considered, it is the best data governance software and a staggering majority of its users have showered high praise on G2.

Key features and capabilities: 

• Data governance policies: Create org-wide governance policies using fully customizable templates and upload them. This eliminates errors and guesswork associated with policy framework mapping by automatically mapping to selected frameworks. 

• Data access security: Set up role-based access management for critical system data that aligns with your security framework using adaptive policies and flexible review mechanisms to ensure frictionless access and complete compliance. The system auto-authenticates based on role, risk level, and the principle of least privilege. 
• Streamline governance program: Runs a well connected and fully automated data infosec governance program through continuous control monitoring, high fidelity and context rich alerts, and granular view of risks. 
• Customize features: Offers highly customizable capabilities to manage data infosec like custom security standards, controls, and checks. IT teams can add and expand the scope of governance via controls as needed, automating the custom controls, which normally cannot be automated. 
• Automate controls: Highly responsive integrations and automation facilitates better control aggregation and higher reliability of tests. Alerts teams of failures with context to ensure on time remediation. 
• Manage data risks: Infosec risk assessment helps to visualize the true impact of data risks using industry benchmarks to help teams systematically manage risks. The system precisely and accurately surfaces vulnerabilities and misconfigurations that threaten data integrity. 
• Control mapping: Maps risks to security controls, runs automated checks to test control health, flags anomalous behavior and triggers remediation workflows. It also offers a built-in escalation matrix to ensure the stakeholders in charge of a control are informed when SLAs are missed. 

Checkout: How Sprinto helped Happay automate boost compliance efficiency

Pros 

• Automates compliance steps that would otherwise require manual effort, documentation, and paperwork
• Integrates seamlessly with business systems like GSuite, AWS, Github, Google Cloud, etc
• Comes with built-in features such as policies, security training, organizational charts, and device monitoring
• Ready-to-launch security programs for over 20 data governance and privacy frameworks, including custom ones.
• Pre-built policy templates and training modules with in-app acknowledgments
• Pre-mapped controls and checks for comprehensive compliance coverage
• Real-time compliance via automated checks and pre-configured workflows
• Fully automates evidence collection for quick and effortless audit readiness
• Confidently navigate audits with a dedicated dashboard for collaborative evidence review
• Guided platform implementation with white-glove support from setup to management 

Cons 

• Does not support on-premise systems

Get a fully automated data governance and privacy compliance tool. Talk to our experts. 

G2 rating: 4.8/5

Egnyte

Egnyte enables users to collaborate securely by deploying multi factor mobile device management. It allows users to set granular permissions to secure files, identifies suspicious downloads, and organizes files using machine-generated metadata.

Egnyte’s AI powered content intelligence engine allows users to converse with private data sets using GPT models, detect unusual behavior, and train AI models on private data.

IT teams and security administrators can use Egnyte to manage content risks such as accidental data loss, data exfiltration, noncompliance with regulatory requirements, poor lifecycle management, and more.

Key features and offerings: 

• Structures unstructured personal data by locating them, automatically attaches metadata to sensitive files using AI, programmatically monitors data flows, and prioritizes risk mitigation activities. 
• Adds granularity and context awareness to access controls, maintains logs of sensitive files, automatically deletes redundant files, protects PII using encryption techniques, and restricts access based on geolocation.
• Evaluate response actions to incidents, automate access request management, ensure transparency to handle personal data, and track privacy impact assessments through predefined workflows. 
• The unified control dashboard classifies and continuously monitors sensitive data using out of the box classification patterns. Proactively detects and prevents unauthorized access and suspicious login attempts. 

Pros 

• Strong encryption and granular access control capabilities secures data and minimizes breaches
• Simple to set up and deploy, enabling easy transition from local server-based systems to cloud storage
• High scalability and flexibility boosts productivity in diverse work environments
• Model-agnostic architecture facilitates using any AI model 

Cons 

• Unexpected charges and lack of transparency in billing practices
• Slower upload speeds for larger files hampers productivity 
• The interface refreshes when navigating back from viewing a file, disrupting workflow

G2 rating: 4.4/5

MineOS

MineOS enables organizations to process their AI assets in a secure, private and compliant way.  Users can quickly launch fully automated privacy programs that include DSAR (Data Subject Access Requests) handling, consent management, and data mapping.

The dashboard shows all AI data sources from SaaS vendors who use AI in some features. The comprehensive dashboard view shows the location of each asset, their owner, security posture of the systems, and if vendors developing an AI feature are compliant.

Key features and offerings: 

• MineOS’s discovery technology continuously and securely scans emails, cloud hosted apps, and websites to show a complete picture of data using in AI tools
• Assess AI vendors to comply with data privacy frameworks like GDPR. Teams can build custom assessments for internal projects that use AI and ML. 
• Assesses risks associated with data processing based on the app’s purpose, data sources, and AI characteristics to generate an estimate of AI’s impact on your business
• Governs data flow across AI tools based on custom policies. Triggers alerts to notify teams if non-compliant data is detected

Pros

• The robust automation features for DSARs, data mapping, and compliance tracking, saves time and resources
• Many reviews highlight the intuitive UI and straightforward integrations that enables teams to implement and use with no hassles
• Users consistently commend MineOS for its responsive and helpful support team
• Centralizes and simplifies data privacy workflows, especially for DSAR handling and managing privacy compliance

Cons

• Some integrations are not seamless and may need additional API development
• Limited customization capabilities such as the request intake form and response templates
• Data mapping can be time-consuming and overwhelming for some users, especially in complex organizational setups

G2 rating: 4.8/5

IBM data governance

IBM’s data governance module helps users meet privacy and compliance requirements using AI and machine learning capabilities. It improves data quality by analyzing statistics and data quality scores to ensure quality. 

Its data privacy tool reduces the risk of noncompliance by identifying sensitive data and enforcing protection controls. The tool also simplifies and streamlines data accessibility and product life cycle management. 

Key features and offerings: 

• Identifies enterprise data assets using intelligent recommendations and adds context to data by automatically contextualizing assets from the data catalog.
• Uses machine learning powered data quality rules to automate data profiling and assign quality scores.
• Creates custom governance workflows to create a review, approval, and publication process. The policy management system helps to manage compliance and protect data.
• Runs automated risk assessments, creates a risk verified data library, generates GDPR grade risk identification metrics based scores, and improves risk assessment efficiency using a centralized dashboard.

Pros 

• Users praise its exceptional capability to manage and integrate metadata assets which helps to centralize business metadata 
• The powerful data lineage feature helps both business and technical users
• Supports custom attributes and a broad range of integration, making it adaptable for unique needs
• The user-friendly interface enables both administrators and users to operate seamlessly

Cons 

• Some users faced frequent server issues and lack of strong technical support 
• Lacks plugins to connect with other ETL tools and fails to capture metadata from other tools
• The pricing module is not small business friendly but fits the budget for large organizations 

G2 rating: 4.0/5

OneTrust Privacy and Data Governance Cloud

OneTrust Privacy and Data Governance Cloud helps businesses gain regulatory agility by using a proactive approach based on privacy best practices rather than reactive responses to regulations. It helps IT teams make risk-backed decisions through enhanced visibility into unknown risks, triggering reassessment when changes happen.

Key features and offerings: 

• Automates Data Protection Impact Assessment (DPIA) distribution and analysis process to help users achieve privacy by design
• Determines and minimizes risks through enhanced visibility, collaborative workflows, and controls to implement privacy best practices, escalates Privacy Impact Assessment (PIA) with risk to DPIA
• Automatically flags risks based on its severity, likelihood, and recommends corrective actions. Contextualizes data, operationalises risk activities, and unlocks opportunities for governance automation capabilities. 
• Seamlessly connects with apps using flexible pre-built connectors and bulk import tools to facilitate data visibility. 
• Flags policy violation by discovering data in non-confidential systems and out-of-the-box data classification methods
• Discovers and categorizes sensitive data using AI capabilities, monitors for data drift, identifies unencrypted passwords or keys, and remediates using integration workflows.  

Must check: 8 Data Governance Challenges That Can Derail Your Business Success

Pros 

• Compartmentalises assessment based on framework and uses AI to discover and classify data
• The platform is frequently updated to accommodate new technologies and compliance requirements
• Detailed assessment workflows integrate seamlessly with existing processes
• Offers a variety of dashboards and easy-to-create custom reports and templates

Cons

• UI is outdated, not user friendly, and the navigation is often confusing
• Lack of pre-configured workflows requires meticulous planning and collaboration to implement the modules successfully
• Some user reported slowed performance and unresponsiveness while managing large volumes of data

G2 rating: 4.3/5

SAP Master Data Governance (MDG)

SAP Master Data Governance’s platform’s tightly controlled workflow processes streamline data distribution, eliminate manual data maintenance, identify gaps in the consistency of legacy data, and improve data quality across the enterprise. 

Its enhanced security program helps companies reduce risks, boost productivity, and future proof their businesses through a structured governance system. 

Their SAP Datasphere module supports comprehensive data solutions that improves forecasting accuracy, drive stakeholder analytics, and provides deeper insights into the vertical market. 

Key features and offerings: 

• Consolidates SAP and third-party data sources to offer a single source of truth. Processes large volumes of data to provide bulk updates.
• It empowers teams to create custom master data sets and use validated values for data points through collaborative workflow routing and alerts. 
• Offers a centralized hub for mid-scale businesses to decentralize, consolidate, create, change, and distribute domain-specific master data across the enterprise infrastructure
• Defines, verifies, and monitors business policies to check master data readiness and analyze its performance using a single platform. 
• Adds operational efficiency in master data management through centralization and harmonization. Builds a network of data governance systems and runs them in coordinated processes to facilitate efficient management of the master data. 

Pros 

• It is well integrated with SAP solutions to facilitate reusing of data models, business logic, and validation frameworks. 
• Supports customization and configuration based on business needs
• Reduces data redundancy by eliminating duplicate data
• Provides a single, trusted source for all critical business data

Cons 

• The setup and implementation process is time-consuming and resource-intensive
• Integrating the MDG with non-SAP systems can be complicated
• Separate licensing and customization costs may not be suitable for smaller companies

G2 rating: 4.4/5

Atlan

Atlan eliminates complications associated with data governance processes using a community-centered, privacy-based approach. It collaborates metadata from multiple sources to help teams discover, catalog, and govern data. 

Altan’s “copilot for data” offers a wide range of AI capabilities, such as data discovery through natural language searches, simplifying complex SQL transformations, handling complex SQL queries, and generating documents for new data sets. 

Key features and offerings: 

• The “Purpose” feature allows users to define policies, curate project-specific data, organize public financial KPIs, and mask PII data to prevent unauthorized access. It adds granularity to asset access policies based on user roles.
• Contextualizes data facilitates data browsing on search engines, builds trust by streamlining compliance, and automated metadata enrichment
• It offers complete visibility to data assets using tables, metrics, dashboards, and models. It surfaces data based on popularity, automatically nullifies sensitive data based on access policies, and uses column-level lineage tracking. 
• Offers a single source of truth across functions, links assets to business metrics, facilitates SQL syntax searches, and conducts impact analysis using custom metadata. 

Pros 

• The intuitive and modern UI simplifies onboarding and daily use even for users from a non-technical background
• Users appreciate the wide range of supported integrations for tools like Chrome extension and Slack
• AI-powered capabilities add efficiency to data discovery processes
• AI and natural language processing capabilities contextualize complex data sets 
• Robust metadata management includes usage analytics, lineage tracking, and AI-generated suggestions for table and column descriptions

Cons 

• Reporting capabilities are not adequately customizable
• Despite its user-friendly interface, there is an initial learning curve for some of the advanced features
• Outdated documentation and absence of readily available bug fixes and information 
• Some users mention that the tool is often to load detailed information about data assets

G2 rating: 4.6/5

Satori

Satori helps IT teams control access to sensitive data, define rules for interaction, and dynamically apply policies in compliance with security and privacy regulations. The tool works by identifying critical data assets across your infrastructure, defining access based on role or requirements, and anonymizing data by detecting changes. 

Satori uses AI to enable data and security teams to analyze large volumes of data, quickly surface information, and secretly transfer it. This includes sensitive data like PII, PHI, and PCI. 

Key features and offerings: 

• Helps organizations embrace AI transformation by enforcing security and privacy compliance policies. Offers out of the box compliance policies, protects data even when users violate restrictions, and automates access management for machine learning stack. 
• Continuously scans the data repository to identify assets that don’t have the right permissions or have the necessary access controls to reduce risk exposure. 
• Automatically enforces security policies on sensitive data using dynamic processes like data type, owner, users, and context of usage. Users can define a custom classification taxonomy specific to their purpose. 

Pros: 

• Many users highlight the robust security features and the peace of mind it provides
• The support team is often praised for being responsive and helpful
• Simple and intuitive user interface
• Saves a significant amount of time by automating processes like data structuring 
• The tool integrates with various data store with ease

Cons

• Some users felt that the pricing structure shared with them lacked transparency 
• The initial set process can be somewhat complex

G2 rating: 4.8/5

Collibra 

Collibra combines data cataloging, governance, and privacy into a single platform. The tool continuously monitors data health and quality, contextualizes data, enforces governance policies, visualizes data flow, and assess regulatory risks. It helps businesses accelerate their performance by offering useful insights into their data assets and transforming its usage across the data landscape. 

Key features and offerings: 

• Classifies sensitive data using out of the box polices custom to specific use cases, automatically enforces data quality rules. Uses generative AI to write complex data quality rules and reuses rule templates to quickly develop custom data quality rules
• Analyzes data pipeline health across business units and data sources to identify blindspots in operations and quarantine incidents that may interrupt business operations.
• Users can create, review, manage, and update data policies using a centralized system to maintain compliance and increase transparency while minimizing risks. 
• Uses advanced algorithms to classify sensitive data, enhance accuracy and operationalize privacy regulatory requirements.
• Discovers and assesses risks across data management processes and maintains a data inventory of sensitive data.

Pros: 

• Simplifies collaboration among data stakeholders
• Offers comprehensive data cataloging and metadata management capabilities
• The interface is user friendly and integrates easily with existing systems
• Can be customized to fit a wide range of use cases and scales with growing needs

Cons: 

• The price module is not suitable smaller companies and startups
• Performance takes a hit with large volumes of data sets and consumes high amount of resources
• Setting up user permissions is cumbersome and initial configuration can be complex

G2 rating: 4.2/5

Segment

Segment enables businesses to make data-driven decisions by collecting, unifying, and transferring customer data into the right system to contextualize it and facilitate data-driven decision-making. 

Users can mask sensitive data using code, automate data validation processes like testing tracking codes, detect and classify personal information, block data based on privacy policies, and standardize data to ensure consistency.

Key features and offerings: 

• Offers a unified platform for clean and accurate customer data by breaking down siloed systems and enables users to customize the platform using developer toolkits.
• Ensures compliance with data regulations to minimize regulatory risks and prevents sensitive data collection such as PII. 
• Creates a centralized data inventory  that blocks collecting and sharing of sensitive customer data. The consent manages helps to ensure transparency with customers. 
• Simplifies compliance with data privacy frameworks like HIPAA to protect PHI and PII by validating data quality violations, unifying patient data across platforms, and automates data quality best practices to ensure data hygiene and reliability 

Pros

• Real-time data processing and analytics aids in decision making
• Detailed insights into customer behavior aids marketing strategy implementation
• Tracks user’s events on websites at a granular level 
• Supports detailed user segmentation for targeted marketing strategies

Cons

• The user interface can be clunky and sometimes difficult to navigate
• Lacks a robust funnel analysis abilities compared to competitors 
• Some users mentioned the lack of granularity in funnel tracking features

G2 rating: 4.5/5

Key considerations to choose the right tool

When choosing a data governance tool, look for agile software with capabilities and convenience, response API connectors, and adaptability to your business and security requirements.

Here are the key considerations to choose the right tool:

Evaluate tool features and capabilities

When analyzing the available tools in the market, start by comparing the key features and functionalities, including:

• Data discovery and classification: The tool must automatically discover and catalog data from various sources for  an up-to-date inventory
• Automated quality checks: It must automatically enforce rules for data consistency, completeness, and accuracy
• Data lineage tracking: The tool must visually represent the data flow across systems
• Role-based access controls: It should support access permission management to safeguard sensitive information
• Policy management and automation: It must support automated compliance policy enforcement 

Ensure seamless integrations

Ensure the tool integrates with your current infrastructure, including databases, third-party applications and cloud environment. If it offers native integrations and custom APIs, you’ll get instant time to value along with enhanced automation and efficiency.

Check for flexibility and scalability

As organizations increasingly rely on data for business operations and decisions, the data management must scale quickly. You need a tool that can grow with data volume, variety, and velocity without causing performance issues. Similarly, a flexible tool with customization options enhances its adaptability over time without requiring you to make major changes.

Run a product trial

Take a product trial to evaluate whether the tool delivers on its promises, is user-friendly and compatible, has any technical limitations that could hinder implementation, and can handle custom use cases. This will provide valuable insights to support your final decision.

Consider costs and ROI

Calculate the direct and indirect cost of ownership, including license fee, implementation costs, training, product maintenance, and ongoing support. Compare it with the long-term benefits, including enhanced data quality, compliance, and operational efficiency, to build an ROI case before selection.

Research vendor reviews

Gain insights on how the tool performs for similar businesses by researching for vendor reviews and case studies. Look for positive and negative sentiments on vendor support and service to get a clear picture on the product value.

Benefits of data governance tools

Data governance tools help minimize misconfigurations, compliance gaps, data replication, and data decentralization, which enhances the overall efficiency of operations and helps maximize business value.

The following are the benefits of data governance tools:

Integrated approach to data management

Data governance tools provide a coordinated and integrated approach to managing data, ensuring that different departments do not work with siloed data or duplicate efforts. Instead, the data is centrally managed while ensuring compliance with privacy laws, protecting it from unauthorized access, and maintaining consistency and quality throughout its lifecycle.

Enhanced decision making

Data governance tools make data easily accessible from a centralized location, ensuring quality and consistency across departments. This enhances the reliability and trustworthiness of the data, leading to faster insights and improved decision-making

Compliance Management

Data governance tools automate the implementation of controls such as access controls, and data encryption while generating detailed audit trails to track activities across data management. These platforms also continuously monitor data usage and identify compliance risks to enable the organization to stay compliant with privacy laws such as GDPR or HIPAA.

Reduced operational costs

Data governance tools minimize any redundant data management efforts thereby reducing costs of storing duplicate data. Next, they automate a range of tasks such as data classification, compliance checks and continuous monitoring and reduce manual efforts and costs. Lastly, the tools streamline workflows for enhanced operational efficiency leading to lower operational overheads.

Cost of data governance tools

Data governance platforms are a broad category that covers a wide range of tools. As their capabilities and target buyers differ, so does the pricing module. A small to mid-sized company can expect to pay between $20000 and $100000 annually and $150000+ for a large company.

Pricing can include components such as licensing fees, hosting prices, add-on costs, and maintenance costs. Sometimes, the pricing structure can also be variable and dependent on the number of users.

Here are some examples of pricing structures:

• Egnyte tool has three plans with variable pricing: Business plan priced at $20 a month per user, enterprise lite priced at $38 a month per user and and enterprise plan with custom pricing.
• Satori on the other hand, starts at $70000 subscription a year as a base plan and the highest subscription goes upto $150000 a year.

Having said that, speaking from experience of having worked with thousands of companies of all sizes, we can vouch for this—it is never a good idea to prioritize cost over quality or use it as one of the main criteria for choosing a tool. 

You can use our cost calculator to estimate how much setting up an infosec governance program would cost you.  

Sprinto – One tool to govern them all

Remember the story at the beginning? Well, data regulations are becoming more stringent by the day. And if Facebook cannot escape them, neither can you. However, implementing complex regulations is not easy. If you try to handle things manually, it can quickly spiral into chaos. 

So what if there was a tool that organized everything for you, ensured you were compliant without missing a beat, and did all the heavy lifting for governance activities? 

Sprinto is an end to end data governance, risk management, and privacy compliance tool that helps you implement, manage, and monitor all your data from a centralized solution. With Sprinto, you can:

• Monitor your data in real time for non compliance, vulnerabilities, and anomalous behavior 
• Get alerted to quickly patch issues to ensure continuous compliance using AI based recommendations
• Create and maintain a risk library to scope out risks specific to your business. Mitigate risks proactively and map them to the right controls 
• Use a single dashboard to manage, create, share, and policies using pre built library of template – so you don’t have to write a policy from scratch, ever again

Still on the fence? Get a personalized demo to discuss your goals. 

FAQs

What is data governance?

Data governance is the practice of managing and organizing data within an organization in a way that ensures compliance with data regulations. It involves creating policies, procedures, and standards to ensure that data is secure, accurate, and accessible. 

How do Data Governance Tools handle data privacy?

Data governance tools manage privacy by monitoring, controlling, and reporting on the data lifecycle based on policies and compliance requirements. They work by enforcing policies and procedures to ensure compliance with regulations, implementing data masking and encryption, managing access controls, monitoring data usage, and auditing activities. 

How can I choose a data governance solution?

To choose a data governance solution, ensure it has the following capabilities: 

• Compliance audit readiness
• Governance strategy builder 
• Digital transformation
• Access control management
• Cloud Integration capabilities
• Accurate analytics of data quality 
• Surfaces wide range of risks 
• Policy enforcement