Data classification is the process of organizing information assets using an agreed-upon categorization, taxonomy or ontology. The result is typically a large repository of metadata useful for making further decisions. This can include the application of a tag or label to a data object to facilitate its use and governance, either through the application of controls during its life cycle, or the activation of metadata using data fabric.
By Deepti Gopal, Sema Yuce, Michael Kranawetter – Source
Extensive Policy RepositoryOur software includes a vast repository of over 1300 global privacy policies, covering 40+ native languages. This extensive range allows for immediate, accurate classification across diverse data types and regions, eliminating the need for time-consuming language translation.
Customizable Classification RulesTailor your data classification to fit your unique needs. Our system allows you to mix, match, and modify existing policies to create new classification rules. This customization ensures a precise fit for your company’s specific data environment
Setting Confidence Levels and Unique Count MinimumsGain control over classification accuracy. Adjust the confidence level to balance between precision and coverage, and set the unique count minimum to minimize false positives. This flexibility helps fine-tune the system to your organization’s data landscape.
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Initial Training with Machine LearningOur system begins with a robust machine learning model, pre-trained to understand a broad spectrum of data types. This foundational training ensures highly accurate data identification and classification from the outset.
End-User Validation of ClassificationsWe emphasize flexibility by offering optional features for end-users to validate machine learning-generated classifications. This alignment with your business’s unique requirements guarantees that our automated processes are tailor-made for your needs.
Continuous Machine Learning ValidationThe innovation continues unabated! Our application perpetually validates and refines its classifications via ongoing machine learning. This dynamic approach maintains data classification accuracy, ensuring it stays current and adapts to evolving data patterns and organizational shifts.
Machine Learning, Validation of Detected, Classification
SituationA leading global bank, operating in regions with stringent auditing and data compliance standards, faced the intricate task of managing and classifying a wide range of data effectively.
ChallengeThe bank was confronted with the challenge of scanning, classifying, and managing both structured and unstructured data across various platforms. This task was intensified by the need to adhere to the strict auditing and data protection regulations specific to some of the regions it operated in.
SolutionData443 Data Identification Manager provided an ideal solution. It offered an extensive array of over 1300+ built-in rules in 40+ languages, which the bank initially used for data classifications. The bank also capitalized on our solution's flexibility to create custom text and regex rules, further refining the classification process to meet their unique requirements. This allowed the bank to effectively classify data across an array of repositories, such as SQL Server, SAP, Oracle, MongoDB, MySQL, and various file systems and network shares. A key advantage of our solution was its integration capabilities, enabling the bank to link their PowerBI instance for enhanced data analytics and reporting. Additionally, the solution facilitated seamless mapping with Microsoft AIP and CyberArc, offering robust security and efficient access management across the bank’s data repositories.
OutcomeThe implementation of Data Identification Manager notably improved the bank's data governance, security, and compliance frameworks. The solution's adaptability, coupled with its robust built-in rules, allowed for a custom and efficient data classification system. This comprehensive approach not only ensured compliance with regional data protection and auditing standards but also streamlined their data management processes, significantly boosting operational efficiency. By utilizing the Data Identification Manager, our customer successfully addressed complex data classification challenges and regulatory changes in the banking sector.