What is unstructured data?

Unstructured data is any information that doesn’t follow a predefined format. It can be an entire file, like a slide presentation, or a section within a document, such as a paragraph in a report. Often known as content, this type of data comes in multiple formats, including PDFs, videos, audio clips, and images.

Think about all the information that you can’t drop into a spreadsheet or database. Invoices, sales proposals, and meeting recordings are examples of unstructured content. And in your business, it likely makes up most of your files. According to Congruity360, about 90% of data in the digital universe is unstructured.

This amount of raw information is a goldmine of untapped value, but it’s often spread across cloud storage and document management systems, making it hard to access and use. The good news: you can harness your content’s potential and turn it into actionable insights for your organization. Keep reading to discover how.

Key highlights:

• Unstructured data is information that doesn’t follow a fixed format, such as call recordings from your support team or campaign files from marketing efforts
• Unstructured data examples in business include emails, contracts, reports, financial records, and archived backups
• The main difference between structured and unstructured data is format — structured information has a fixed model that’s easy to analyze, while unstructured data requires more advanced tools for processing and use
• Box, the Intelligent Content Management platform, helps turn unstructured information into valuable insights through AI-powered capabilities, workflow automation, and app integrations that fit the way teams work

Key characteristics of unstructured data

Lack of uniformity is just one of the characteristics of unstructured data. You can also describe it as:

• Subjective in meaning: Unstructured data doesn’t follow a fixed format, so its meaning often depends on tone, layout, or phrasing. For example, a sentence in a transcript might imply urgency based on tone, while a customer review might sound positive or negative depending on the words surrounding a single phrase.
• Vast and diverse: Businesses manage large volumes of unstructured content on a daily basis, and in multiple formats. For example, you can integrate personalized welcome messages, training guides, forms, and introductory videos into an onboarding workflow.
• Difficult to analyze: Content without structure or metadata (contextual information like dates and document types) often requires artificial intelligence (AI) to capture key information and interpret tone and sentiment. Traditional solutions like enterprise content management (ECM) systems require users to add metadata manually, a process that takes time and limits data extraction.

See why businesses are moving from legacy ECM to Intelligent Content Management..

Examples of unstructured data in business

Unstructured data is the lifeblood of your business, impacting every team, system, and workflow. Here’s where it appears in your day-to-day operations.

• Emails and attachments with internal communications and client conversations
• Customer support transcripts, such as live chat logs and call recordings
• Marketing assets like creative visuals and campaign files
• Contracts and agreements, such as vendor terms and legal documents
• Reports and presentations like strategy decks and status updates
• Financial documents, such as bank statements and audit files
• Resumes and training materials in formats like PDFs, slides, and videos
• Data backups, which include archived logs and legacy files

Structured vs. unstructured data: Understand the differences

In most organizations, content management involves capturing, storing, and using structured and unstructured data. While one powers day-to-day transactions, reporting, and other critical activities that depend on consistent file formatting, the other helps you capture the context and knowledge to support decision-making.

Let’s compare structured vs. unstructured data to outline the differences between these two types of content.

Besides structured and unstructured data, you can categorize content as semi-structured, which means it’s organized but not locked into a fixed format. For example, hypertext markup language (HTML) helps structure information on a website with tags like headings and paragraphs, but the information inside these tags isn’t strictly structured.

How does unstructured data impact business decision-making?

Unstructured data can help explain the “why” behind your metrics and records, so you can make decisions with a deeper understanding of the context. Let’s say your sales numbers show a drop in revenue, and customer service chat logs reveal that competitors are offering lower prices. Your structured data shows what happened, while an unstructured source of information explains why.

With the growing adoption of AI, the way businesses manage unstructured data has changed. The Association for Intelligent Information Management (AIIM) found that 90% of organizations expect AI to impact how they work with unstructured file formats. AI-powered platforms can retrieve, capture, and analyze data at scale and with high precision, speeding up decision-making.

Tasks that once took hours in your operations now happen in minutes or even seconds with AI for unstructured data. For example, this technology can:

• Convert scanned PDFs into searchable, structured formats
• Summarize complex reports into key takeaways
• Match resumes to job descriptions in the hiring process
• Categorize documents by project or department in content portals

Discover how AI-powered content portals help surface and manage your business data.

Is big data unstructured?

Big data refers to datasets, including structured, semi-structured, and unstructured data, that are so large, complex, and quickly generated that traditional tools can’t effectively process or analyze them to extract valuable insights.

Imagine an enterprise generating hundreds of chat messages, documents, photos, and transaction records every day. Without scalable cloud data storage, this company would quickly reach its capacity limits and have difficulty processing the constant flow of unstructured big data.

How is unstructured data stored?

The way you store unstructured data varies depending on the type of content, how often you need to access it, and the systems and tools your business already uses.

The best examples of unstructured data storage include:

• High-capacity cloud storage: Best for housing large volumes of unstructured data without stressing your local infrastructure. Choose this option when you need flexible access to large data sets like video archives or engineering files.
• Digital asset library: Built for teams that rely on rich media. This system allows you to easily organize, find, and collaborate on campaign visuals and product shots.
• Records management system: A secure way to organize sensitive documents that come with legal or compliance obligations. Go with this solution for storing vendor agreements and financial records with strict retention schedules.
• Intelligent Content Management platform: An AI-powered unstructured data platform to manage files at scale, using content intelligence to get more value from business information. It’s a cost effective way to bring AI into content creation, search, analysis, and automation, while connecting the apps you already use for more efficient data workflows.

Top 3 challenges of storing and managing unstructured data

Unstructured data management can only be effective if your teams are able to find and collaborate on files without accidentally exposing sensitive information to breaches and compliance violations. But achieving this balance of usability and governance isn’t always easy.

Below are three of the most critical challenges of storing and managing unstructured data and practical ways to address each one.

Challenge #1: Rapid data growth requires governance and security

The “scalability versus data security” dilemma keeps CIOs and IT leaders awake at night, especially as the volume of unstructured data grows. When you have a vast amount of content in different formats and sensitivity levels, how can you manage the data lifecycle at scale without compromising protection or compliance?

Solution

Combining flexible storage with built in data governance and security controls is the way to start when considering platforms. Look for solutions that let you define custom policies, apply encryption, and control access at a granular level to meet regulatory standards.

Challenge #2: Data silos slow down collaboration

Even if your unstructured content platform provides secure collaboration tools, they can’t be fully useful when data is scattered across systems. Teams waste valuable time searching for the information they need, hindering collaboration and reducing overall productivity.

Solution

Cloud app integration connects tools and software your teams use into one content layer. For example, you can pull information from your CRM into document templates and send a contract for electronic signature without leaving the CRM system.

See how to integrate e-signatures into your content workflows. 

Challenge #3: AI integration depends on accessible, unstructured data

Together, unstructured data and AI can reveal hidden patterns and contextual intelligence that structured data can’t do alone. But when your information isn’t organized or accessible, AI algorithms can’t analyze it effectively. An IDC study reveals that poor data access and/or quality negatively impact the success rates of generative AI implementations.

Solution

Investing in intelligent solutions that organize and secure unstructured information paves the way for effective and responsible AI implementation. Prioritize advanced platforms that clean data, eliminating redundancies and inconsistencies to make it easily accessible. Reliable tools also give you control over what AI models can or can’t train on.

Review the AI principles you should consider when integrating this technology.

Unstructured data management best practices for businesses

To keep your unstructured database organized and ready for AI integration, focus on these best practices.

• Create a strategy for enterprise metadata management: Capture and extract key data across all your unstructured content to enhance searchability and analysis.
• Automate data entry and processing: Use AI workflow automation tools to ingest unstructured information from your documents, PDFs, and images, routing them to the right location — for example, a dashboard or an approval queue.
• Enable secure access from anywhere: In the State of AI in the Enterprise report from Box, 73% of organizations named data security and compliance as the top priority when selecting an AI platform for content and unstructured data. Let your teams access files securely across locations through cloud-based solutions with multi-factor authentication (MFA), encryption, and audit trails for regulatory compliance.

Manage your unstructured data storage securely and intelligently with Box

There are powerful insights hidden within your business files. To uncover them, you need an unstructured data platform that helps you organize, search, and secure information without slowing your team down. Box, the leader in Intelligent Content Management, helps you turn data into intelligence your business can act on.

With our platform, you get:

• A flexible and interoperable solution to store and manage unstructured content easily, while protecting the flow of information with security and compliance controls
• Box AI, our suite of AI-powered capabilities that quickly extract key data and deliver contextual insights and answers based on your documents
• AI-powered workflow automation to streamline processes like onboarding and document routing to keep your operations running smoothly and efficiently
• Seamless integration with over 1,500 apps, enabling your teams to collaborate across different tools without leaving Box

Reach out to our team and discover how Box can help you get more value from your unstructured data.

*While we maintain our steadfast commitment to offering products and services with best-in-class privacy, security, and compliance, the information provided in this blog post is not intended to constitute legal advice. We strongly encourage prospective and current customers to perform their own due diligence when assessing compliance with applicable laws.