Skip to content

Fighting dark data with Artificial Intelligence

[acf field="subtitle"]

Fighting dark data with Artificial Intelligence

[acf field="subtitle"]

In today's data-driven world, managing unstructured data is a huge challenge for companies. This so-called 'dark data', information that remains unused or untapped, not only represents a missed opportunity for organisations but can also pose risks. With the use of advanced artificial intelligence (AI) and automatic classification, these challenges can be solved. Find out how to use these technologies to combat dark data and increase the efficiency and effectiveness of your data management.

The problem of Dark Data

Dark data is the information that companies generate during regular business activities but that is not actively used for decision-making, tasks or other purposes. This can range from old documents and e-mails to unstructured data in, for example, a CRM system. 

The information, documents and data are called 'dark' because basically no one in the organisation knows exactly where it is and how to find or use it. It is hidden data, as it were.

These 'blind spots' in information management create a number of risks:

  • Wasted resources
    Organisations spend huge budgets collecting and storing data, but if this data is not used, the investments are wasted. In addition, the cost of storing this data (possibly unnecessarily) can be huge.

  • Missed opportunities
    Dark data can contain valuable insights and opportunities that can help organisations grow, cut costs and increase competitiveness. By not exploiting it, organisations are missing out on these opportunities.

  • Compliance risks
    Dark data may contain sensitive information, such as personal or financial data, which must be protected under regulations such as the General Data Protection Regulation (GDPR). Failure to adequately manage dark data can lead to compliance risks.

  • Operational inefficiencies
    Unorganised dark data can make it difficult to quickly access relevant information, leading to delays and inefficiencies in business processes.

How AI helps fight Dark Data

To combat dark data, it is crucial to deploy modern technology. One of the most promising technologies in this regard is artificial intelligence (AI). AI can perform tasks that normally require human intelligence, such as pattern recognition, classification and analysis of large amounts of data.

M-Files uses AI to tackle dark data in different ways:

  • Auto rating
    The AI algorithm can automatically classify documents and data based on content, metadata and context. This allows M-Files to identify and structure dark data, making it easily accessible.

  • Search optimisation
    Through its AI-driven search algorithm, M-Files can help find relevant information even in large amounts of dark data. This improves efficiency and productivity.

  • Pattern recognition
    AI can recognise patterns and trends in dark data, which can provide valuable insights for decision-making and strategic planning.

Thus, one of the core components of the M-Files approach to dark data is auto-classification. Auto-classification is the process of using AI to automatically label and categorise documents and data based on their content and context. 

Auto-classification offers several advantages:

  • Efficiency
    Manual classification of data is time-consuming and error-prone. With auto-classification, organisations can organise data much faster and more accurately.

  • Consistency
    Auto-classification ensures uniform and consistent labels and categories, reducing confusion and improving collaboration.

  • Scalability
    Using AI, organisations can classify large amounts of data, regardless of the size of their archives.

  • Locations
    Thanks to M-Files' technology, various (external) sources can be searched. Think of network drives, SharePoint, Microsoft Azure, but also e-mail archives and CRM systems.

  • Cost savings
    Reducing manual classification tasks can lead to significant cost savings in the long run.

Practical applications of auto classification

Then the practice. How does M-Files apply AI and auto-classification to transform dark data into valuable sources of information?

  • Email management
    Many organisations struggle with the abundance of unstructured emails that can be considered dark data. M-Files can deploy AI to classify emails based on content and attachments, giving users quick access to important correspondence.

  • Contract management
    Contracts are often complex and time-sensitive documents that contain important information. M-Files can automatically classify contracts and extract relevant data such as expiry dates, parties and conditions, making contract management more efficient.

  • Information security
    Dark data may contain sensitive information that needs to be protected. M-Files can use AI to identify and tag sensitive data, allowing organisations to better comply with regulations and secure their data.

  • Compliance
    By labelling information, automatic workflows can be set up. For example, consider a retention policy that automatically deletes or archives certain documents.

  • Reporting and analysis
    M-Files can analyse dark data and identify trends and patterns thanks to AI. This enables organisations to make more informed decisions and gain strategic insights.

Dark data poses significant challenges for organisations of all sizes and sectors. Leaving this hidden treasure trove of information untapped can lead to missed opportunities, inefficiencies and compliance risks. M-Files offers a powerful and efficient solution to combat dark data through artificial intelligence and auto-classification.

Take the first step against dark data today and Try M-Files for free.

Read also

Back to all items.

Knowledge files

In today's data-driven world, managing unstructured data is a huge challenge for companies. This so-called 'dark data', information that remains unused or untapped, not only represents a missed opportunity for organisations but can also pose risks. With the use of advanced artificial intelligence (AI) and automatic classification, these challenges can be solved. Find out how to use these technologies to combat dark data and increase the efficiency and effectiveness of your data management.

The problem of Dark Data

Dark data is the information that companies generate during regular business activities but that is not actively used for decision-making, tasks or other purposes. This can range from old documents and e-mails to unstructured data in, for example, a CRM system. 

The information, documents and data are called 'dark' because basically no one in the organisation knows exactly where it is and how to find or use it. It is hidden data, as it were.

These 'blind spots' in information management create a number of risks:

  • Wasted resources
    Organisations spend huge budgets collecting and storing data, but if this data is not used, the investments are wasted. In addition, the cost of storing this data (possibly unnecessarily) can be huge.

  • Missed opportunities
    Dark data can contain valuable insights and opportunities that can help organisations grow, cut costs and increase competitiveness. By not exploiting it, organisations are missing out on these opportunities.

  • Compliance risks
    Dark data may contain sensitive information, such as personal or financial data, which must be protected under regulations such as the General Data Protection Regulation (GDPR). Failure to adequately manage dark data can lead to compliance risks.

  • Operational inefficiencies
    Unorganised dark data can make it difficult to quickly access relevant information, leading to delays and inefficiencies in business processes.

How AI helps fight Dark Data

To combat dark data, it is crucial to deploy modern technology. One of the most promising technologies in this regard is artificial intelligence (AI). AI can perform tasks that normally require human intelligence, such as pattern recognition, classification and analysis of large amounts of data.

M-Files uses AI to tackle dark data in different ways:

  • Auto rating
    The AI algorithm can automatically classify documents and data based on content, metadata and context. This allows M-Files to identify and structure dark data, making it easily accessible.

  • Search optimisation
    Through its AI-driven search algorithm, M-Files can help find relevant information even in large amounts of dark data. This improves efficiency and productivity.

  • Pattern recognition
    AI can recognise patterns and trends in dark data, which can provide valuable insights for decision-making and strategic planning.

Thus, one of the core components of the M-Files approach to dark data is auto-classification. Auto-classification is the process of using AI to automatically label and categorise documents and data based on their content and context. 

Auto-classification offers several advantages:

  • Efficiency
    Manual classification of data is time-consuming and error-prone. With auto-classification, organisations can organise data much faster and more accurately.

  • Consistency
    Auto-classification ensures uniform and consistent labels and categories, reducing confusion and improving collaboration.

  • Scalability
    Using AI, organisations can classify large amounts of data, regardless of the size of their archives.

  • Locations
    Thanks to M-Files' technology, various (external) sources can be searched. Think of network drives, SharePoint, Microsoft Azure, but also e-mail archives and CRM systems.

  • Cost savings
    Reducing manual classification tasks can lead to significant cost savings in the long run.

Practical applications of auto classification

Then the practice. How does M-Files apply AI and auto-classification to transform dark data into valuable sources of information?

  • Email management
    Many organisations struggle with the abundance of unstructured emails that can be considered dark data. M-Files can deploy AI to classify emails based on content and attachments, giving users quick access to important correspondence.

  • Contract management
    Contracts are often complex and time-sensitive documents that contain important information. M-Files can automatically classify contracts and extract relevant data such as expiry dates, parties and conditions, making contract management more efficient.

  • Information security
    Dark data may contain sensitive information that needs to be protected. M-Files can use AI to identify and tag sensitive data, allowing organisations to better comply with regulations and secure their data.

  • Compliance
    By labelling information, automatic workflows can be set up. For example, consider a retention policy that automatically deletes or archives certain documents.

  • Reporting and analysis
    M-Files can analyse dark data and identify trends and patterns thanks to AI. This enables organisations to make more informed decisions and gain strategic insights.

Dark data poses significant challenges for organisations of all sizes and sectors. Leaving this hidden treasure trove of information untapped can lead to missed opportunities, inefficiencies and compliance risks. M-Files offers a powerful and efficient solution to combat dark data through artificial intelligence and auto-classification.

Take the first step against dark data today and Try M-Files for free.

Knowledge files
Read also

Back to all items.

Back To Top