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Data classification

Dataconomy

Data classification is a critical aspect of data management that not only enhances efficiency but also strengthens security protocols. As businesses increasingly depend on data, having a structured approach to handling this information becomes essential. What is data classification?

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Sensitive information

Dataconomy

Sensitive information plays a pivotal role in our interconnected digital world, where data flows freely across platforms and borders. Understanding what constitutes sensitive information, and how to protect it, is essential for individuals and organizations alike. What is sensitive information?

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Data Classification: Overview, Types, and Examples

Pickl AI

Summary: Feeling overwhelmed by your data? Data classification is the key to organization and security. This blog explores what data classification is, its benefits, and different approaches to categorize your information. Introduction In today’s digital age, information is king.

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What is Data Classification? Guidelines, Types, & Examples

Alation

Data classification is necessary for leveraging data effectively and efficiently. Effective data classification helps mitigate risk, maintain governance and compliance, improve efficiencies, and help businesses understand and better use data. Manual Data Classification. Labeling the asset.

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Discover the universe of Gamma AI for better protection

Dataconomy

The business’s solution makes use of AI to continually monitor personnel and deliver event-driven security awareness training in order to prevent data theft. The cloud-based DLP solution from Gamma AI uses cutting-edge deep learning for contextual perception to achieve a data classification accuracy of 99.5%.

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Data Classification Can Make or Break Data Governance

Dataversity

The news these days is full of massive fines levied against companies that failed to protect their customer data. An effective data classification approach is one of the best ways to ensure that companies can identify and protect their most valuable data. Our experience continues to […].

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It’s time to shelve unused data

Dataconomy

The purpose of data archiving is to ensure that important information is not lost or corrupted over time and to reduce the cost and complexity of managing large amounts of data on primary storage systems. Artificial intelligence (AI) can be used to automate and optimize the data archiving process.