Microsoft

Structured vs. Unstructured Data: Keys to Success

Steven Osprey, Chief Technologist
Steven Osprey, Chief Technologist

Data isn’t just data: it’s the heart of your business.

It doesn’t matter what industry you’re in – finance, architecture, construction, retail – what matters is how your data is being stored and translated by both your customers and your employees.

Although you may believe your data is safe, secure, and organised, the truth is data is a lot more complex than that. For example, think about your desktop folders. Do you have folders with rogue documents with company data in? Can these be accessed by other employees easily? Can you extract meaningful data from them, or would you have to chase around for other documents to get the information you need?

The world is deeply interconnected, continues to get more interconnected every day, and as a result, the sheer volume of data generated daily is staggering.

Amid this data deluge, businesses are also confronted with the challenge of managing and extracting meaningful insights from two distinct types of data: unstructured and structured.

What the Statistics Say About Your Data

Research shows that a mere 20% of a business’ data is structured, neatly organised in databases and spreadsheets, easily searchable and analysable. The remaining 80% is unstructured, a rapidly expanding category encompassing emails, videos, audio files, documents, and images. This unstructured data is not a dormant asset; rather, it’s a treasure trove of knowledge and insights.

Mid-market sized businesses often find themselves housing between 4 to 10 million documents, each potentially holding valuable information. Yet, this wealth of data presents significant challenges. Users frequently struggle to locate and utilise the insights buried within these files. IT Directors and CIOs grapple with the daunting task of governing this data and ensuring compliance. Meanwhile, CTOs and CEOs face the hurdle of leveraging this data to drive their business forward.

The growth of unstructured data is a testament to the dynamic nature of modern business communications and operations. However, it also underscores the pressing need for sophisticated tools and strategies to manage, analyse, and extract value from this vast and varied information landscape.

Can you say with confidence that your data is easy to find, easy to access by relevant users and secure from outside threats? If the answer is no, you need to assess how you can change this.

 

What is Structured Data?

Structured data is the solid backbone of organised information systems.

When we talk about structured data, we mean information that follows a specific, already laid-out format. This makes it easier to organise and process on a daily basis. Think of structured data as a library: the words are the data, the books are the context and the library itself is the ‘structure’. The structure is the shelves and the order they’re placed in.

Structured data plays nice with databases and spreadsheets because it follows a particular schema. This means that structured data can fit right into these systems without a problem.

 

So, what are some notable characteristics of structured data?

First, there’s consistency. Every piece of data follows the same rules and structure, no surprises. Then there’s organisation – it’s neatly arranged in tables, rows, and columns. This makes it easy to store and find what we need when we need it. Finally, there’s accessibility – it’s simple to get the information, update it, and analyse it. No hassle, no fuss.

In fact, take a look at TSG Mosaic – the perfect example of how we help you to organise your unstructured data by wrapping a structured data system around it.

Examples of Structured Data

Structured data is all over the place in various industries and applications. You’ll find it in:

Databases: The likes of MySQL, Oracle, and SQL Server are the go-to for storing structured data in tables. It makes querying and manipulating data easy.

Spreadsheets: Tools like Microsoft Excel and Google Sheets let users tidy up data in rows and columns, providing a neat format for all your numbers and words.

CRM Systems: Customer Relationship Management (CRM) software keeps customer data, sales transactions, and interactions in order. It’s like a structured treasure trove for businesses managing customer relationships.

E-commerce Platforms: Online shops make good use of structured data to keep product listings, prices, customer orders, and inventory levels in check. It ensures smooth sailing for transactions and order fulfilment.

Why Should You Care About Structured Data?

Structured data offers several advantages that facilitate streamlined data management and reliable analysis:

  • Easy organisation: Thanks to structured data’s tabular format, organising things is a piece of cake. You can systematically categorise, sort, and filter information based on whatever criteria you need.
  • Efficient processing: Structured data gets processed like lightning using database management systems. Queries and operations on this data are fine-tuned for speed, ensuring you can retrieve and play around with your data in the blink of an eye.
  • Reliable analysis: The consistent structure of structured data is like a superhero cape for data integrity. It slashes the risk of errors during analysis, so researchers and analysts can trust the consistency of the data format. That leads to rock-solid insights and decision-making.

Understanding the nuances of structured data is essential for businesses seeking to optimise their data-driven processes.

 

What is Unstructured Data?

Unstructured data is exactly that – it’s essentially any data that lacks a clear, organised structure. Unlike structured data, which fits neatly into databases and spreadsheets, unstructured data doesn’t adhere to a specific structure.

As above, we compared structured data to a ‘library’, think of unstructured data as the pile of magazines, books, notepads you’ve scattered in various places like your cupboards, cars, bags, etc. It’s disorganised and there’s different kinds of written content.

Have you come across any of these before?

  • No/lack of organisation: Unstructured data does not follow a uniform format, making it difficult to categorise or organise systematically.
  • Many different formats: Unstructured data comes in various forms, such as text content, images and video files, social media posts, and sensor data, further complicating its management and analysis.
  • Difficult to understand: Extracting meaningful insights from unstructured data often requires sophisticated techniques like Natural Language Processing (NLP) and machine learning algorithms due to its complexity and variability.

 

Examples of Unstructured Data

Without realising it, right now you’re reading a piece of unstructured data – this article. You’re most likely working with unstructured data every day. Some of these examples are (but are not limited to):

Emails: Email communications contain unstructured data in the form of free-text messages, making it challenging to extract valuable insights without advanced analysis techniques.

Social Media Posts: Platforms like X (previously Twitter), Facebook and Instagram generate unstructured data through user posts, comments, and multimedia content, reflecting diverse opinions and sentiments.

Images: Image files – whether photos, diagrams, or scanned documents – carry unstructured data that requires image recognition technologies for analysis and interpretation.

Videos: Video content, ranging from security camera footage to online tutorials, contains unstructured data that demands video analysis tools for content understanding and pattern recognition.

 

Why You’ll be Hearing All About Structured and Unstructured Data

The conversation around unstructured data has become increasingly prevalent, and for good reason. Unstructured data presents significant challenges not only for compliance and productivity but also stands as a formidable barrier to the more advanced realms of automation, business intelligence (BI), and artificial intelligence (AI).

Without a structured framework, data remains chaotic and elusive, defying the very rules and systems necessary to automate processes, extract meaningful insights, or apply reasoning to create and innovate.

To delve deeper into this topic and explore the solutions, we invite you to join our upcoming webinar. It’s an opportunity to understand how you can turn the tide against unstructured data and leverage it to your advantage.

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