Can you truly trust your data?
If you or your team hesitates before answering, you’re not alone. Many organizations struggle with understanding what data they have, where it resides, and whether it’s reliable. Without proper documentation, data quickly becomes fragmented, outdated, or even misleading, and potentially leading to missed opportunities and poor decision-making.
And that’s why we’re introducing our End-to-End Data Quality Series! 
Data is one of the most valuable assets for any organization, but without a strong quality framework, it can quickly become unreliable and untrustworthy. In this four-part series, we’ll walk through the essential steps of achieving high-quality, trustworthy data—from documenting your data landscape to preventing issues before they arise. Each post will break down a key stage of the framework and providing actionable insights.
Please do join in the discussion in the comments, let us know if you have followed any of these tips, or what helped you in your DQ journey 
Let’s kick things off with the first step: understanding and documenting your data!
Data quality starts with knowing what you have. Before you can trust and leverage your data, you need to document it—understanding where it resides, who owns it, and how it flows through your systems. This process helps uncover sensitive data (like PII), establish ownership, and create a single source of truth.
Key capabilities that support this include a data catalog, which acts as a central hub for data discovery, and a business glossary, which links technical metadata to business terms. Additionally, data lineage (keep an eye on Product Updates soon for some exciting news🤫) provides a visual map of how data moves through the organization, ensuring transparency and compliance.
By investing in structured data documentation, organizations can set a solid foundation for quality and governance. But it’s not just about documentation—it’s about making data findable, understandable, and actionable.
How does your organization handle data discovery and ownership? Are there any challenges in achieving full transparency? Let’s discuss!