Structured versus Unstructured Data
11 July 2025
In the techie world we have long had a core understanding of the differences between structured data and unstructured data and in the business world most business leaders have not had any need to really understand and deep dive into the differences. Data was Data.
In today's Business World Unstructured Data is the untapped corporate goldmine and with silver linings that are sometimes already used and other times difficult to reach.
What is the difference?
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Structured data is organized and often entered and stored in predefined formats—thinks forms that you enter, data that is defined per field, rows (such as the rows and columns in a Spreadsheet like Excel or rows and columns in relational databases (The customer tables in Dynamics 365 or transactions in SQL).
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Unstructured data is everything else: created documents, PowerPoint presentations, emails, social media posts, chat transcripts, video, voice, other types of documents—anything not neatly organized or that might be mixed.
Why
Why is this important to understand? Why is the positioning of structured and unstructured data such a great topic in today's world?
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Structured data powers applications such as the Accounting software of the world (aka ERPs), and the Customer Relationship Management Software (CRMs), and predictions surfaced in dashboards or reports. It’s essential for traditional analytics, regulatory reporting, and core business functions. Business applications traditionally run on structured data and although they have long provided access to some unstructured data, it was not easily consumed or used.
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Unstructured data is the untapped corporate goldmine. It holds deep insights about customer's through e-mail interactions, captured tone and sentiment, product feedback, market trends, historical relationships, deep research reports and perhaps even other "tool" predictions given that format could be different.
One power of AI (Azure OpenAI, GenAI, OpenAI, etc.) is in leveraging the unstructured data goldmine and combining or using unstructured and structured data.
Deeper Thinking
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Artificial Intelligence and Machine Learning (AI/ML) and products designed using AI (Copilots) thrive on unstructured data. Large Language Models (LLMs) (like the secure Azure OpenAI models) are trained on unstructured text. The emergence of tools like Microsoft Copilots (140+), Microsoft Agents and Azure Cognitive Search are all about interpreting and acting on unstructured content.
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In the world of Microsoft Fabric - Data lakes and lake houses have blurred the lines—organizations now store all types of data together for flexible analytics using platforms like Microsoft Fabric or Azure Synapse or other vendor products.
One area that is more advanced and that humans (consulting for instance) comes into play is with Compliance and governance. Compliance and Governance is more complex. Structured data is easier to audit; unstructured data often hides sensitive content and requires new tools for classification, data loss prevention (DLP), redundancy, and security.
In Summary:
“Structured data keeps your engine running. Unstructured data shows you where to steer next. In this AI-first world, the winning formula is intelligent integration—where insight, trust, and action converge.” Anne Stanton