Understanding Your Data: The Key to Trust and Business Success

Better decision-making, innovation, and compliance all hinge on one common factor: trusted data. And today, we’re working with more data than ever.

But here’s a fundamental challenge that many organizations face – and one I’ve encountered in countless conversations with customers: they don’t fully understand what data they have, let alone whether they can trust it.

This point was driven home in our 2025 Outlook: Data Integrity Trends and Insights report, which found that 67% of leading data and analytics professionals don’t completely trust the data that their organization uses for decision-making.

This lack of clarity in data discovery and assessment creates real consequences, like  inefficiencies, increased risks, and missed opportunities.

The High Cost of Not Knowing Your Data

When you don’t have a clear understanding of your data landscape – what data exists, how trustworthy it is, etc. – it opens your organization up to several risks:

• Unreliable analytics and AI (artificial intelligence) Poor data quality results in flawed insights. That leads to costly business mistakes.
• Wasted resources: Teams spend excessive time searching for and verifying data. When more time is spent reacting  to data challenges, it prevents you from being proactive in using that data to drive better outcomes for the business. The result? Missed opportunities and organizational fatigue.
• Regulatory and compliance pitfalls: In industries with strict data governance requirements, missing or unreliable data can result in hefty fines and legal penalties.
• Revenue loss and brand damage: Untrustworthy data can degrade customer experiences. This can trigger a lack of confidence, customer churn, and negative brand perception.

How Leaders Can Take Control of Their Data

If your organization finds itself facing these risks or others like them, there’s good news: with the right approach to data discovery and assessment, you can take back control. It all comes down to proactivity.

Here are some of the best practices we’ve seen work time and again:

1. Implement a comprehensive data catalog: A centralized data catalog gives your teams clear visibility into all data assets – including metadata, lineage, and usage – so they can quickly locate and understand their data.
2. Use trust scores: By continuously assessing data quality, you’re able to identify and address inconsistencies before they impact business decisions.
3. Establish data ownership and governance: Clear governance frameworks ensure accountability and maintain the integrity of your enterprise data. Then, it’s easier to trust and use that data effectively across the business.
4. Leverage AI-driven discovery tools: Advanced AI-powered solutions can help you improve accuracy and reduce the manual work involved with data classification, discovery, and relationship mapping.

The Path Forward: Build a Foundation of Trust in Your Data

If there’s one message I want business leaders to take away, it’s this: the responsibility of understanding and trusting your data goes beyond your IT teams. It’s a critical, strategic step for you to prioritize in the journey to making smarter data-driven decisions that drive meaningful results.

By implementing robust discovery and assessment strategies, you ensure that data-driven initiatives are built on a foundation of trust, accuracy, and accessibility.

So, are you ready to gain clarity and confidence in your data?

Now is the time to invest in discovery and assessment strategies that empower informed decision-making and drive sustainable business success.

To get started in understanding your data, download our checklist: Building Data Confidence: A Checklist for Reliable Insights. You’ll find the actionable steps you need to take to gain visibility into your data and build trust in your decision-making processes.