Common challenges in data management and how Ohalo Data X-Ray can solve them.

POINT1

Files are scattered across on-premises and cloud environments, making it difficult to track the location of confidential data. As a result, excessive access permissions and inappropriate file sharing occur.

Visualizing distributed sensitive data

It scans across on-premises and cloud environments, providing continuous visibility into the location of distributed sensitive data.

POINT2

Traditional DLP relies on regular expression or dictionary-based detection, which often leads to false positives and over-detection, increasing the operational burden.

High-precision data classification using generative AI

Generative AI classifies and detects sensitive data with high accuracy, regardless of format or language.

POINT3

Although Microsoft Purview's confidentiality labels have been implemented, there is considerable inconsistency in classification criteria among individuals, and many classification errors occur, rendering the system largely ineffective.

Automated assignment of sensitivity labels (Purview integration)

The classification results are integrated with Microsoft Purview to automate the assignment of sensitivity labels. This enables encryption and access control based on the labels.

It is said that 80% to 90% of the data held by companies is unstructured data.
Among these, file data, primarily Office files such as Word, Excel, and PowerPoint, contains a large amount of important information that forms the core of corporate activities, including customer information, contracts, intellectual property, management documents, and investor relations information.

This data is created, updated, and shared during daily operations, and its storage locations are scattered across cloud storage such as SharePoint, OneDrive, and Google Drive, as well as on-premises file servers. As a result, it becomes difficult to accurately grasp "where important data is located, what kind of data it is, and who has access to it," making it easy for excessive permissions or unintended disclosures to be left unaddressed. This can lead to serious risks such as information leaks due to internal fraud or accidental errors, and even unintended information leaks when using AI.

An effective approach to these challenges is the DSPM (Data Security Posture Management) approach. DSPM is a system that discovers and classifies data within an organization, visualizes confidential information and access rights, and continuously identifies and evaluates security risks starting from data.

Ohalo Data X-Ray: Flexible and highly accurate file classification using generative AI technology.

Ohalo Data X-Ray is an unstructured data-focused DSPM solution that provides cross-sectional visibility into millions to hundreds of millions of file data within an organization. It scans distributed environments, from on-premises file servers to various IaaS and SaaS applications, and automatically discovers files in connectable data sources.

Furthermore, by utilizing AI generation technology to classify files based on their content, we can achieve highly accurate classification even for files that were difficult to classify using conventional methods such as regular expressions and keyword matching, such as contracts and proposals with inconsistent formats, personal information with varying methods of presentation, and documents written in foreign languages.

What is Ohalo Data X-Ray?

A data security platform that provides centralized visibility into unstructured data within an organization.

File classification by generating AI

Flexible file classification, independent of the file format, language used, or specific keywords.

Flexible labeling in accordance with internal information management rules

Combine classification results and access rights using AND/OR conditions to create flexible labeling policies.

Ohalo Data X-Ray × Microsoft Purview Sensitivity Label: Data Protection Utilizing Classification Information

The file classification results from Ohalo Data X-Ray can be automatically integrated with Microsoft Purview's sensitivity labels.

This means:

• Even if a label is not set when the file is created, an appropriate label will be automatically assigned.
• Reduces variations in labels and missed settings caused by manual configuration.
• Based on the label, file encryption and access control are applied using Purview policies.

This enables the following operational procedures.

Furthermore, as the business use of generating AI expands, there are increasing cases where AI accesses internal company data, making the security of the data accessed by AI a critical issue.
Data with appropriately applied secrecy labels reduces the risk of unintended information access or external sharing by AI through access control and restrictions on sharing scope.

The integration of Ohalo Data X-Ray and Purview Confidence Labels goes beyond traditional data leakage prevention, contributing to strengthened data governance in the age of AI.

Integration with Microsoft Purview's sensitivity labeling

Ohalo's classification results are automatically applied to sensitivity labels.