Anomalo is best suited for organizations with modern data stacks that want a standalone, AI-first data quality solution to integrate with broader data management tools. View Anomalo’s detailed scorecard. Collibra Collibra is widely known for its data governance and catalog offerings. It introduced data quality capabilities as a result of its acquisition of OwlDQ, which it offers as a self-hosted data quality tool.

High-quality, trusted data is critical for the success of all enterprise initiatives. Data is a strategic asset that drives decision-making, innovation, customer engagement, and revenue. In Forrester’s Data And Analytics Survey, 2025, data and analytics decision-makers most often cited improving data quality and reliability as being part of their organization’s data governance efforts. This highlights the indispensable role of data quality in enterprise strategy.

Teams build governance maturity in layers. Most begin with cataloging, classification, and lineage, then expand into quality, access workflows, and business-facing features. Smaller teams often accelerate rollout through vendor services, while modular platforms support integration of external tools like data quality scoring. Early pilots, including curated marketplace views and glossary-powered LLMs, enable a pragmatic, step-by-step approach.

Its Data Integrity Suite is a modular, end-to-end platform that integrates governance, quality, enrichment, and observability to drive measurable business outcomes. Strategy. Precisely’s vision is to unify data governance with quality, enrichment, and spatial analytics into a single, accessible platform.

For its marketplace, data is more tightly controlled to meet quality, regulatory, and privacy policies to share data outside the organization. Break your data governance effort down into purpose, culture, and action: Purpose: Know why you need data governance. Data ownership is one of the top questions Forrester clients have about data governance: IT vs. business, employee vs. leader. But that puts the cart before the horse. Purpose is defined by the objective.

Forrester’s 2024 data shows that only 26% of global data and analytics decision-makers say that their company always uses data and insights to make decisions. By enhancing data quality and democratizing data access, modern governance tools lay the groundwork for informed business decision-making. These solutions cater to a broad range of personas, from data stewards to end users, empowering them to leverage strategic insights confidently. Streamline data management and accelerate time to value.

Figure 3 Data Governance Tools Focus On Security And Quality In 2024 Data security, quality, and stewardship technologies are top of mind for data and analytics decision-makers: 71% of respondents said they currently use data security and privacy tools, while 63% said they use data quality and cleansing tools, demonstrating a commitment to the data security and integrity that is foundational to data governance (see Figure 4).

Read this report to understand the intersection of data governance and sustainability data management and reporting — and how data governance is crucial in gaining accurate, transparent, and high-quality data.

Data Quality Technology Adoption The majority of data and analytics decision-makers have or are implementing data quality tools as a type of data governance technology. This graphic has an associated spreadsheet that includes all data presented. Please access the spreadsheet for details. Figure 5

Treat data quality and measurement as growth prerequisites, not support functions. B2B marketing leaders consistently point to improving buyer, customer, and partner data quality as a top support need for marketing priorities (39% overall; EUR: 33% vs. non-EUR: 42%), underscoring data as foundational infrastructure rather than a back-office concern (see Figure 10).