Data intelligence meets value governance: Inside DataGalaxy’s next-gen platform

Enterprises expect more than simply knowing what data assets exist. Today, they demand clear insight into how those assets are being used and what value they deliver.

Therefore, organisations that treat data merely as a technical asset risk leaving business value on the table.

In this blog post, we’ll explore how you can elevate your data initiatives by shifting from a metadata-centric mindset to one built around value governance. We’ll also show how DataGalaxy enables precisely that.

Note: The article references an external opinion piece, “DataGalaxy Addresses the Governance and Value of Data,” originally written by Matt Aslett. View the article here.

Data usage & value, not just discovery

A modern data intelligence catalog helps business leaders understand where and how data is used across an enterprise.

Therefore, treating data as a business discipline (not merely an IT domain) is essential to align data projects with strategic business objectives.

Yet even with these insights, many organizations still struggle with a critical gap. They may know what data they have and who owns it, but they struggle to track how it is being used and what value is being generated by data and AI initiatives.

For example, the recent analysis by ISG highlighted that more than two-fifths of respondents cite measuring ROI as a key data challenge.

When data strategy is defined by IT platforms rather than business outcomes, initiatives risk becoming detached from business value.

In short: the next frontier is not simply cataloging data, it’s governing it for business value.

Why the shift from metadata to value governance matters

Modern enterprises have been investing in cataloging, lineage, glossaries, and governance for good reason.

However, as the complexity of data landscapes, analytics, and AI grows, so must our view of what a data governance and catalog ecosystem should deliver.

Operationalizing

CDEs

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When you shift your mindset to value governance, you:

• Connect strategy to execution: Aligning data initiatives with business domains, objectives, and programs
• Embed governance and product-discipline into data & AI just like any other business product
• Prioritize, monitor, and measure data initiative value in terms of usage, cost, risk, and realized benefit
• Ensure that the data catalogue isn’t just a repository of assets, but becomes the cockpit from which business, analytics, and data teams collaborate, deliver, and assess value

This shift matters because metrics around usage and value increasingly separate “good” from “great” data intelligence solutions.

If your organisation aspires to drive measurable business impact from data and AI — not just tactical wins — you need a platform that bridges catalog, governance, and value measurement.

DataGalaxy for unifying catalog, governance, and value

DataGalaxy connects two powerful products, the DataGalaxy Catalog and DataGalaxy Portfolio, into an end-to-end governance platform designed to organize, govern, and track the business impact of your data and AI initiatives, all in one place.

Unlike legacy catalogs that focus on technical documentation or rigid enforcement, DataGalaxy empowers every stakeholder, from C-suite to business user, to contribute to and benefit from metadata knowledge that is tied directly to measurable business value.

Why focus on value?

There are three compelling reasons:

1. In the AI era, your choice is value creation or value destruction: Without a clear strategy, governance, and sequencing plan, AI investments can squander time and money
2. DataGalaxy is the only governance tool that includes built-in portfolio management to prove and maximise the connection between data, metadata, and business value
3. DataGalaxy rejects governance tools that lock down data and only focus on compliance: Governance must enable, not disable. DataGalaxy turns control into opportunity.

The DataGalaxy difference

• Persona-driven experience: DataGalaxy delivers role-based views, aligning all stakeholders in one collaborative environment
• Visual Knowledge Studio (VKS): A fast, visual workspace that turns siloed data into clear stories, enabling technical and business users alike to understand and act
• Business value mapping: DataGalaxy connects metadata to measurable business outcomes. With built-in portfolio management, you see how trusted data becomes AI-ready, productised, and impactful.

Here’s how the platform delivers across three interlocking layers:

1. Strategy Cockpit & Product Hub

The Strategy Cockpit allows enterprises to capture ideas across the business, organize them into domains or strategic programs, and assess them according to key attributes: strategic alignment, value, effort, and risk.

This means data initiatives don’t live in a vacuum. They are linked directly to business priorities, and you gain a portfolio-based view of your data & AI investment.

Through the Product Hub, datasets, analytics, and AI models become managed “data products”: discoverable, reusable, documented.

2. Automated Data Catalog

The platform’s catalog layer enables you to centralise all data assets, build lineage automatically, enrich metadata with business context, and deliver a “Google-style” search for users across the business.

Features include:

• Smart search to find tables, KPIs, dashboards, definitions, owners, and certifications
• Automated glossary generation (including multilingual support)
• Column-level lineage across tools, browser extension for context in BI dashboards
• 70+ connectors to modern data platforms (Snowflake, Databricks, Power BI, BigQuery, etc.)

3. Governance Hub & Value Tracking

Governance in DataGalaxy is designed for real-world impact, not just documentation.

You can define policies, assign roles, launch governance campaigns, run impact analysis, monitor compliance, and connect usage/cost/value metrics back to your data initiatives.

Together, these three layers provide a unified value governance platform, enabling organizations to move from “What data do we have?” to “How are we using it?” to finally, “What business value are we realizing?”.

Designing data & AI products that deliver business value

To truly derive value from AI, it’s not enough to just have the technology.

• Clear strategy
• Reasonable rules for managing data
• Focus on building useful data products

Read the free white paper

The need for value governance now

There are multiple compelling reasons why organisations should be investing in tools like DataGalaxy today:

Complexity & scale of data and AI initiatives are growing

With increasing cloud adoption, analytics and AI initiatives proliferate across departments.

Traditional catalog or governance tools struggle to keep up. The era of “just a data catalog” is over — organisations need full-service data & analytics governance platforms.

Business scrutiny over data ROI is intensifying

Executives increasingly expect data and analytics initiatives to tie back to business value.

IT-only data strategies are no longer sufficient

When data is treated purely as an IT problem, it risks misalignment with business objectives.

The ISG study showed a nearly even split between the view that data operations should be separate from IT, and the reality that they often remain within IT’s domain.

A platform that enables business and IT-stakeholder collaboration across strategy, governance, and value delivery is essential.

Innovation & compliance demands are rising together

With regulatory mandates (GDPR, CPRA, AI Act, etc.) and business demands for speed and innovation, organisations need a governance platform that supports both control and agility, enabling trusted data use for analytics and AI.

DataGalaxy’s governance hub addresses this balance: control and enablement.

Real-world benefits: What organisations can expect

By shifting your data governance approach to one of value governance and using a platform such as DataGalaxy, you can expect to unlock benefits that map directly to business impact:

• Better prioritisation of data & AI initiatives: With a portfolio view and evaluation scoring (value/effort/risk), you deploy resources where they matter most
  
  
• Improved data discovery, trust & collaboration: Self-service access to data with business context, lineage, and ownership breaks down silos and speeds decision-making
  
  
• Stronger alignment of data projects with business KPIs: Initiatives are directly connected to business domains and strategic objectives, not isolated IT projects
  
  
• Measurable tracking of value and usage: Initiatives move from vague “data projects” to business-governed products with cost, usage, benefit, and risk metrics
  
  
• Governance that scales with adoption: By embedding policies, roles, and workflows into the everyday experience of users (via the catalog, browser extension, campaign workflows), governance becomes part of the business flow rather than a hindrance

Centralize all your data assets in one unified platform, automatically build and maintain lineage across systems, and enrich every asset with AI-powered context. With DataGalaxy, teams can quickly search, discover, and understand the data they need, while ensuring full traceability and trust.

A call to action for data leaders

If you’ve already done the work of cataloging data assets and embedding governance fundamentals, the next step is to ask, “Are we capturing and measuring business value from our data and AI initiatives?”

As you evaluate the landscape of data intelligence and governance providers, here are key questions to ask — and where DataGalaxy stands out:

• Do we have a strategy cockpit for data and AI initiatives that links to business domains and objectives?
• Can we assess initiatives by value, risk, effort, and track progress over time?
• Does our data catalog integrate both business users and technical users, with lineage, glossary, and metadata enriched with business context?
• Are governance, data products, collaboration, and compliance provided in one platform rather than disparate tools?
• Do we have metrics for usage, cost, and realised value per initiative — not just counts of assets cataloged?

About the author

Jessica Sandifer

With a passion for turning data complexity into clarity, Jessica Sandifer is an experienced content manager who crafts stories that resonate across technical and business audiences. At DataGalaxy, she creates content and product marketing messages that demystify data governance and make AI-readiness actionable.