Tackling the Complexity of Unstructured Data

In today’s digital world, the volume of data being generated by organisations is staggering – and growing exponentially by the day.  

According to Statista, 149 zettabytes of data were created each day in 2024 and by 2028, global data creation is projected to grow to more than 394 zettabytes. IBRS referred to this as ‘information hyperinflation’, a phenomenon fuelled by the widespread use of collaboration tools and the distribution of structured, semi-structured and unstructured data across various business platforms.  

This dramatic rise in data volume poses significant challenges for organisations trying to effectively manage their information assets, let alone prepare their data for upstream processes such as the adoption of responsible AI in the enterprise. 

The reason? An overwhelming proportion of their information assets exist in unstructured formats, making unstructured data analytics and unstructured data processing more critical than ever. 

What is Unstructured Data? 

Unstructured data management refers to information that exists outside of traditional databases and data warehouses. It doesn’t follow any pre-defined data model with rows and columns. Instead, unstructured data encompasses formats like: 

• Documents (PDFs, Word, etc.) 
• Emails and messages 
• Video and audio files 
• Images and multimedia 
• Webpages and online data 
• Sensor and IoT data 

Essentially, unstructured data is information that is disorganised and lacks easily searchable characteristics. This is in contrast to structured data neatly packaged into spreadsheets and databases, as well as semi-structured data like XML files with some organisational properties. 

The Unstructured Data Challenge  

According to IDC, a staggering 90 per cent of organisational data is unstructured. This unstructured information resides across disconnected systems and repositories, creating fragmented “data silos” that lack governance. 

Without the right unstructured data processing, organisations face increasing risks and missed opportunities: 

Data Privacy and Regulatory Compliance Risks 

Sensitive data containing personally identifiable information (PII), payment data and more could be flowing unchecked across these unstructured repositories. Without effective unstructured data management, this creates significant exposure to data breaches, regulatory penalties for non-compliance with data privacy laws like GDPR and CCPA, and damage to brand reputation. 

Challenges for Responsible AI 

Poor data governance and quality stemming from ungoverned, unstructured data leads to AI models that can perpetuate bias, discrimination and harm if deployed. Responsible AI in the enterprise requires understanding and high-quality data used to train models. 

To learn more about Responsible AI, see our blog Responsible AI deployment: the essential role of data management. 

Underutilised Data, Missed Insights 

When a significant portion of an organisation’s data assets are essentially invisible and underleveraged, there is a huge missed opportunity. The business intelligence locked in unstructured data analytics could be fuelling data-driven decisions, optimising operations, identifying new revenue streams, and improving products/services. 

Leveraging AI to Discover Unstructured Data 

As data volumes continue to accelerate, traditional manual processes and legacy content management systems are no longer adequate for the scale and complexity of unstructured data management. What is required are intelligent information management solutions powered by artificial intelligence and machine learning technologies capabilities to automatically process, manage and protect large amounts of data at scale. 

EncompaaS empowers organisations to discover, understand and manage enterprise data by leveraging next-generation AI technologies to find, enrich, organise and de-risk structured, unstructured and semi-structured content anywhere in the enterprise with speed and accuracy.  

By automating the discovery of unstructured data repositories, EncompaaS eliminates dark data, transforming previously invisible and underutilised information into a strategic asset by: 

• Automatically finding and classifying sensitive data to protect privacy 
• Extracting insights and analysing unstructured data for business intelligence
• Enforcing data governance policies  
• Surfacing critical business intelligence using AI-powered data analytics

What’s more, by normalising all organisational data into a foundation of high-quality data, compliance and privacy obligations – including the application of retention and disposition policies – can be addressed automatically at-scale to de-risk the enterprise. With rapid provisioning of the EncompaaS SaaS platform into business environments, organisations can increase time to value and more easily connect new systems as required with an extensible connector framework – without the need for costly upgrade projects.  

Benefits of Using Unstructured Data  

By intelligently processing unstructured data using advanced AI technologies, organisations can unlock a wealth of benefits, including: 

Mitigating Privacy and Compliance Risks 

Unstructured data processing helps identify and classify sensitive data, ensuring organisations comply with regulatory standards while reducing exposure to breaches. Being able to automatically identify personal data, IP, payment information and more allows organisations to proactively protect this data. 

Fuelling Data-Driven Decision Making 

The ability to extract key data points and context from videos, documents, audio and more surfaces rich intelligence. This can inform strategic decisions across departments from marketing to product to operations. 

Enhancing Customer Experiences 

Analysing sentiment, behaviour patterns and preferences within customer conversations, messages and online content provides a deeper understanding to personalise experiences and improve your products or services. 

Optimising Processes and Reducing Costs 

Insights pulled from unstructured data analytics can reveal patterns in process inefficiencies and areas to streamline workflows and reduce operational costs across the organisation.

Powering Trustworthy AI Initiatives 

To build effective and unbiased AI and machine learning models, organisations need high quality, reliable training data derived from all of their data sources, including unstructured data repositories. By analysing unstructured data and ensuring responsible artificial intelligence, organisations can increase trust in AI systems. 

Unlocking Competitive Advantage 

Ultimately, extracting maximum value from the wealth of proprietary information buried within an organisation’s unstructured data reserves can create competitive advantage by uncovering hidden information value that was previously undiscovered or underutilisied. 

Realising Unstructured Data’s Potential 

With data being generated at an unprecedented rate, organisations can no longer afford to overlook the vast potential of unstructured data.

As we move forward in the digital age, embracing intelligent information management platforms is no longer an option but a necessity. Organisations that embrace AI-driven unstructured data management will be positioned to unearth insights, mitigate risks and enable responsible AI in the enterprise.

To learn how EncompaaS can help your organisation and supercharge information safer, faster and smarter, contact us or book a demo.