Monika Bujanowicz
September 06, 2023
13 min read

Why Is Your Data Classification Not Working (and What to Do About It)

Why Is Data Classification Not Working and What Can You Do About It

Data classification and prioritization are critical for businesses to enhance efficiency, reduce costs, and make informed decisions. However, traditional data classification techniques may not be sufficient due to the ever-growing volume of data being generated. Artificial Intelligence can help tackle this challenge.


This article explains the significance of AI in transforming data classification and processing. It highlights the importance of compliance regulations and the challenges faced in data classification while providing insights on how AI can help overcome them. The blog also outlines the benefits of using AI in data classification, including improved accuracy, security, and reduced risk of unauthorized access.


Lastly, it offers tips on selecting the right AI data company for effective data classification and prioritization. Come along as we explore the fascinating world of AI-powered data classification!





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Why is Proper Data Classification Important in Business?




Accurate data classification is critical for effective decision-making and compliance with regulatory requirements. By categorizing data based on its importance and sensitivity, businesses can prioritize their resources and focus on the most relevant information. Proper data classification also enables efficient data management and organization, leading to improved workflows and streamlined processes. Most importantly, it enhances data security by reducing the risk of unauthorized access and safeguarding the classified information. In summary, data classification is essential for businesses to make informed decisions and maintain a strong security posture.




What are the Different Levels of Data Classification?

The different levels of data classification include:



  • Public data
  • Internal use only
  • Confidential
  • Highly confidential



These levels help organizations determine how sensitive and critical their data is and implement appropriate security measures to protect it.





Data Classification in Decision-Making

Data classification is an essential aspect of decision-making processes. It involves grouping data into categories, which enables decision-makers to identify and prioritize the most critical information required for informed decision-making.


Proper data classification also makes it easier to analyze data, identify trends, and gain insights into patterns that can shape decision-making strategies. Accurate and reliable data is critical in decision-making, and proper data classification ensures that only such data is used, minimizing the risk of errors or misinformation.


Effective data classification ultimately leads to enhanced decision-making efficiency and effectiveness, empowering organizations to make informed choices that drive their success.






Effective data classification ultimately leads to enhanced decision-making efficiency and effectiveness, empowering organizations to make informed choices that drive their success.






Data Classification in Compliance Regulations (GDPR, HIPAA, PCI-DSS)

Proper data classification and backup are crucial for organizations to comply with regulations such as:



  • General Data Protection Regulation (GDPR)
  • Health Insurance Portability and Accountability Act (HIPAA)
  • The Payment Card Industry Data Security Standard (PCI-DSS)




Data classification is a crucial process that assists in identifying and safeguarding sensitive personal information according to its sensitivity level and legal requirements. Adequate security controls are implemented to mitigate the risk of data breaches and unauthorized access.


Compliance with data classification regulations not only protects valuable information such as PHI and credit card numbers but also fosters a secure environment and adherence to industry standards. Regular review and update of data classification policies are necessary to align with the changing regulations.


To maintain confidentiality and comply with compliance regulations, organizations should prioritize the appropriate handling and protection of sensitive data, including email communication. Seeking legal and compliance experts' assistance can guarantee full adherence to relevant regulations, especially in legal discovery.






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Why is Your Data Classification Not Working?




Data classification may not work effectively due to various reasons. It can be hindered by a lack of understanding of its principles and methodologies. Inadequate or incorrect classification can lead to mismanagement and security risks. Different type of data need different methods of handling. Moreover, the absence of standardization and interoperability, as well as insufficient access to high-quality datasets, can impede accurate classification.





Why is Your Data Classification Not Working?





Your data may be someone's intellectual property or personally identifiable information. They may have a problem with your organization accessing or processing set datasets. Even if it was obtained as public data, regulatory compliance is a must. Incorporating AI technologies can help overcome these challenges and improve data classification accuracy.





You Don't Understand Data Classification

Data classification is a critical aspect of organizational security, yet it is often overlooked and underestimated. This can result in ineffective implementation and increased potential risks and complications. Contributing factors to this problem include a lack of awareness, insufficient training, and failure to involve key stakeholders. You must prioritize clear communication and education, as well as involve all relevant parties in decision-making. By doing so, you ensure the security and compliance of information and improv data classification practices.





Your Data Handling Process is Faulty

Inaccurate or insufficient classification of data can have serious implications for businesses, particularly in regard to financial information. If data is poorly labeled and categorized, it can lead to mismanagement and security vulnerabilities, which in turn can result in the exposure of sensitive information such as credit card and social security numbers.


The absence of standardized and consistent data classification procedures can cause confusion and errors that compromise data security. Failure to maintain and update data classification policies and guidelines can lead to incorrect categorization, resulting in compliance violations with regulations such as GDPR and HIPAA. To mitigate these risks, be meticulous and conduct regular audits and reviews to identify and rectify any errors.









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Your Systems are Not Compatible

Interoperability of systems is difficult to achieve due to incompatibilities between different systems. This can lead to inefficiencies, inconsistencies, and difficulties in collaboration and data sharing. To overcome these challenges, it is necessary to establish industry-wide standards and guidelines that promote better standardization and interoperability.


Collaboration and knowledge-sharing among companies also play a big role in improving the efficiency and effectiveness of data classification systems. By working together and adopting common frameworks, your industry can overcome this challenge. The European Union has already established industry standards and guidelines that promote better standardization and interoperability.





Your Datasets Have Errors

Insufficient availability of diverse and high-quality datasets can affect the accuracy of data classification. Biased or incomplete classifications can result from inadequate representation of different data types and categories. However, there are ways to overcome these challenges.


One approach is data discovery, including collaborating with external sources and data providers to access a wider range of quality datasets, including public information. Another method is investing in data cleaning and preprocessing techniques to improve the quality of available datasets.








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No AI in Your Data Loss Prevention (DLP)

The potential benefits of AI-powered technologies like machine learning and natural language processing in improving data classification accuracy are immense. By automating the classification process, AI can significantly reduce human errors and enhance efficiency, while handling large volumes of data and classifying it in real-time.


What makes AI even more valuable is its ability to continuously learn and adapt to evolving data classification requirements. By integrating AI capabilities into data classification systems, organizations can achieve enhanced effectiveness and reliability, including with the use of data loss prevention DLP.















Benefits of AI Data Classification




AI-powered data classification is a game-changer for businesses. The technology offers a host of benefits, the most significant of which is increased efficiency and accuracy in the data classification process. By automating the process, businesses can reduce errors and save time and resources.


Another advantage is enhanced security and privacy, as the systems implement safeguards against unauthorized access and data loss. This helps organizations comply with information security regulations and protect sensitive data. Moreover, by reducing manual data management tasks, AI automation leads to cost savings and improved productivity.





Increased Efficiency and Accuracy

AI data classification has revolutionized the speed and accuracy of data processing. By automating the classification process, human errors are minimized, leading to enhanced efficiency. AI algorithms have the capability to handle large volumes of data swiftly and with precision. Streamlined processes enable faster decision-making, improving overall productivity.








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Reduced Data Entry Processing Errors

Reduced data entry processing errors are a significant benefit of AI-driven data classification. By leveraging AI automation, the risk of human errors in data entry and processing is minimized. With the help of machine learning algorithms, data entry mistakes can be identified and corrected more effectively. Additionally, automated data validation processes reduce the likelihood of inaccurate or incomplete data. This improvement in data integrity and reliability ultimately leads to better decision-making and improved business outcomes.





Increased Security and Privacy

AI-powered data classification has transformed data security and privacy measures, providing enhanced protection against potential breaches. With automated classification, sensitive data is accurately identified and safeguarded, reducing the risk of unauthorized access. AI algorithms excel in detecting patterns and anomalies that may indicate security threats, improving the overall resilience of the system.


Further, AI-driven classifications enable the implementation of advanced security measures such as data encryption and access control, ensuring compliance with confidentiality requirements and industry regulations. By prioritizing security and privacy, organizations can strengthen their defenses and prevent data breaches, building trust among customers and stakeholders alike.





Reduced Risk of Lata loss or Unauthorized Access

Reducing the possibility of data loss or unauthorized access is of utmost importance in today's digital world. AI data classification plays a significant role in this endeavor by aiding in the identification and protection of sensitive data from potential threats coming from the internet or from the inside of the organization.


Businesses can set up security policy and proactively monitor and detect data breaches by using automated classification, ensuring that necessary measures are in place to minimize the chances of unauthorized data access or exposure. AI algorithms can also enforce access controls and authorization based on data sensitivity, further enhancing security measures.





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Reduced Cost and Time Spent on Data Management

Efficient data management is essential for businesses to reduce costs and save time. The use of AI automation can streamline data classification and management processes, resulting in significant time savings. AI algorithms are capable of handling large datasets, minimizing manual efforts and enabling employees to focus on higher-value tasks.


The automation of data classification can help organizations save resources and reduce operational costs associated with data organization. This not only improves efficiency but also increases productivity and optimizes resource utilization.









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Be Like Microsoft: Selecting the Right AI Data Company




When it comes to data classification, selecting the right AI data company is crucial for effective results. World data leaders like Apple, Microsoft, Amazon, and data-handling eBay have excellent data handling capabilities. Observe and learn.


A reliable company should have expertise in classification techniques and offer customizable solutions tailored to your specific needs. It's important to evaluate their track record and customer reviews to ensure reliability, as well as to consider their security measures for protecting sensitive information such as credit card numbers and personal data. Additionally, their data management capabilities are essential, particularly if you need to handle large volumes of data.





Want to experience the benefits of AI data classification for your business? Book a free consultation today. Let us help you unlock the power of your data for better decision-making.





Key Factors to Consider When Choosing an AI Data Company

When it comes to choosing an AI data company for your organization, there are several important factors to keep in mind. Firstly, it's crucial to find a company with experience working with businesses or industries similar to yours, so they have a good understanding of your specific needs and challenges.


It's also essential to assess the company's data classification process and their approach to handling different types of data, including their data protection and encryption measures to ensure optimal security. Scalability and flexibility are additional key considerations, as they determine how well the company's solutions can adapt to your evolving data classification requirements.


Finally, it's important to verify the company's compliance with applicable regulations, such as GDPR and HIPAA, to ensure that your data classification efforts align with legal requirements. By taking these factors into account, you can make an informed decision and select an AI data company that meets your organization's unique data classification needs.






Key Takeaway




Data classification plays a vital role in business. It helps organizations understand their data, make informed choices, and comply with regulations. However, challenges like lack of understanding, inadequate classification, and lack of standardization can hinder its effectiveness.


This is where AI comes in. AI-powered data classification solutions offer increased efficiency, accuracy, security, and reduced risk. They streamline data management processes and save time and costs. When choosing an AI data company, consider factors like expertise, technology, and customer support.





Want to experience the benefits of AI data classification for your business? Book a free consultation today. Let us help you unlock the power of your data for better decision-making.






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