Businesses generate vast amounts of unstructured data from various sources like emails, social media, and other non-traditional formats. This data is particularly vulnerable to security breaches and is challenging to secure. 

Given the sheer volume and diversity of unstructured data, any oversight could lead to catastrophic consequences.. Traditional security measures often fall short in managing and protecting this kind of data. Recognizing the critical need for effective discovery and protection, we have compiled a list of the best unstructured data discovery tools designed for enhancing data security. Let’s begin.

What Is Data Discovery?

Data discovery is a key process used in data governance and analytics. It involves collecting, cleansing, and analyzing electronically stored information to uncover patterns, trends, and insights. This process is crucial for businesses and organizations as it helps make informed decisions based on the data analyzed.

Key Aspects Of Effective Data Discovery

Data discovery is an essential process that helps organizations make the most of their data. Here are the important aspects of data discovery:

• Data sources identification: Identify all potential internal and external data sources, including unstructured and structured data, using specialized discovery tools.
• Data profiling: Assess identified data to determine its structure, quality, completeness, and suitability for analysis.
• Data cataloging: Create a data catalog that offers comprehensive metadata about available data assets, facilitating easy user access.
• Data exploration and visualization: Employ visualization tools to examine data patterns, trends, and outliers, aiding in discovering insights.
• Data relationships and dependencies: Use sensitive data discovery tools to understand the interconnections and dependencies between datasets.
• Data security and compliance considerations: Ensure the identification of sensitive data and compliance with data retention policies and regulations, such as GDPR.
• Data access and governance: Implement strict access controls and governance policies to regulate data usage and lifecycle.
• Data quality assessment: Conduct regular data quality assessments to avoid inaccurate decision-making.
• Iterative process: Approach data discovery as a continuous, iterative process that adapts to new data sources and organizational needs.

Best Unstructured Data Discovery Tools

Since unstructured data increases the cost of e-discovery, employing efficient tools is essential for managing these expenses and complexities. The following tools ensure that every piece of unstructured data is accounted for, protected, and compliant with stringent data protection standards.

1. Strac

Strac stands out among unstructured data discovery tools for its comprehensive approach to sensitive data discovery and classification. The platform is designed to manage unstructured data across SaaS, cloud, and endpoint devices. It supports a wide range of formats, including emails, documents, and multimedia files, which lack a fixed schema or structure.

Key Features

• Sensitive data discovery and classification: Strac excels in locating and classifying sensitive data within unstructured data sources. This capability helps organizations comply with stringent data protection regulations such as GDPR and HIPAA.
• Advanced machine learning and AI integration: By leveraging machine learning algorithms and artificial intelligence, Strac significantly enhances the accuracy and efficiency of the data discovery process. This integration enables the platform to handle the sheer volume and variety of unstructured data storage adeptly.
• Data loss prevention (DLP): The platform offers provides robust DLP functionalities, designed to prevent data breaches by identifying and securing sensitive information.
• Compliance and security: Strac assists organizations in maintaining compliance with major regulatory standards through advanced data scanning tools. It classifies and redacts sensitive data to ensure compliance with security and legal requirements.
• User-friendly integration: Designed for seamless integration with existing systems, Strac facilitates easy adoption with its user-friendly interface.

2. Cohesity

Cohesity leads the field in unstructured data management with innovative solutions like Cohesity SmartFiles and Cohesity DataProtect. These are designed to manage, secure, and leverage unstructured data within enterprise environments. SmartFiles boosts data visibility and accessibility with features like global deduplication and robust security measures against cyber threats.

The platform also excels in data discovery and compliance, leveraging AI to automate sensitive data identification and classification. The solution is scalable and integrates seamlessly with multiple cloud environments, ensuring uniform data management across all platforms. Its flexibility and comprehensive approach make Cohesity a valuable asset for enterprises looking to improve their data management strategies.

3. Rubrik

Rubrik offers advanced capabilities for managing unstructured data through an integrating set of tools for data discovery, protection, and management. It adopts a Zero Trust Security model to ensure robust protection with end-to-end encryption. Notably, features like NAS Cloud Direct deliver air-gapped, immutable backups, which are crucial for rapid data recovery and cybersecurity. 

Furthermore, the tool enhances real-time visibility into data, facilitating efficient archiving and optimization. Its sensitive data discovery feature automates classification and reporting, streamlining regulatory compliance. Rubrik is renowned for its scalability, ease of integration, and its proficiency in securing and managing large volumes of unstructured data effectively.

4. Osano

Osano is a comprehensive data privacy management platform designed to alleviate the complexities of complying with data privacy laws. The platform stands out for its automated sensitive data discovery, which utilizes artificial intelligence to automatically identify and classify personal data across organizational systems. This feature not only saves valuable time but also significantly minimizes the risk of human error.

Users commend Osano for its intuitive interface and the extensive expertise of its team. The platform's automatic site scanning feature continually monitors compliance, effectively managing the challenges associated with third-party cookies and other related elements, particularly in large enterprises. Osano’s emphasis to privacy compliance, alongside its capabilities in data discovery, positions it as an ideal and versatile tool for businesses seeking to efficiently discover and safeguard unstructured data.

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5. Looker

Now an integral part of the Google Cloud Platform, Looker provides powerful capabilities in business intelligence, embedded analytics, and data applications. It provides real-time business insights and allows for sharing these insights through efficient data visualizations and real-time reporting. 

Its seamless integration with Google Cloud's BigQuery optimizes costs and expands access to various data sources. The platform's intuitive interface facilitates the creation of reports, dashboards, and curated content boards, establishing a centralized access point for all data. This makes it an ideal choice for enterprises seeking deep insight into data.

6. Digital Guardian

Digital Guardian is powerful unstructured data discovery software that offers extensive solutions for identifying, classifying, and protecting sensitive data. It excels in integrating deep data discovery with robust data loss prevention (DLP) strategies. It operates across endpoints, networks, and cloud environments by applying advanced algorithms to classify data accurately.

The solution enhances data protection through granular policy enforcement, allowing organizations to customize policies governing data access and sharing. It helps prevent unauthorized data exfiltration and leakage. The analytics and reporting tools provide real-time visibility into data security postures, tracking user activity and potential threats. Digital Guardian’s integration with cloud services also ensures that data protection extends to cloud-based applications and storage.

7. TrustArc

TrustArc is recognized for its comprehensive data privacy management solutions, but it also excels at unstructured data discovery. The platform's integration with BigID boosts TrustArc's ability to manage and discover unstructured data. This partnership enables automated data discovery and privacy program management. It provides crucial insights and transparency into personal and sensitive data under privacy regulations.

It also provides a centralized location for data mapping and risk assessment so that unstructured data can be managed effectively. Additionally, its automated data discovery tools make identifying data collection from various storage locations easier. Utilizing TrustArc improves compliance efficiency, establishes robust risk management, and enhances data insights.

8. CipherTrust Data Security Platform

The CipherTrust Data Security Platform is a leading solution for discovering and securing unstructured data. This platform adeptly integrates advanced features to streamline data discovery, classification, and protection across cloud, big data, and on-premise storage.

It enhances data security with strong encryption and access control measures, ensuring that only authorized personnel can access sensitive data. Additionally, CipherTrust offers comprehensive audit logs and reporting features that aid organizations in complying with data protection regulations like GDPR, PCI DSS, and HIPAA. CipherTrust’s tokenization and sophisticated key management solutions are critical for effectively securing data and meeting privacy requirements.

9. Proofpoint

Proofpoint is unique among unstructured data discovery tools for providing tools to manage and secure unstructured data efficiently. Its capabilities extend beyond basic discovery, incorporating machine learning and advanced visualization tools for in-depth data analysis. Proofpoint Discover, a key product, streamlines e-discovery with capabilities such as advanced data analysis and search within search functionalities. 

Its machine learning technology also automates document review processes, reducing time and costs. Proofpoint's comprehensive approach ensures high security and compliance, making it an essential tool for enterprises managing large sets of sensitive data.

10. Nightfall AI

Nightfall AI aims to offer comprehensive data protection with features like automatic, context-aware encryption and data exfiltration prevention. The platform excels in AI-powered detection to recognize sensitive data across over 100 different file types and contexts. It secures sensitive information across various environments such as SaaS applications, email, and endpoints. 

It effectively reduces false positives in data loss prevention, a common challenge for security teams. Additionally, Nightfall AI can be incorporated into existing systems without causing any complications. It also supports compliance with major standards like HIPAA and SOC 2 to facilitate regulatory compliance.

The Bottom Line

As unstructured data emerges, there is an increased risk of data breaches and compliance failures. It can cause severe repercussions for which securing and managing unstructured data is a must. Keeping sensitive information intact and confidential requires an innovative tool like Strac. By utilizing a comprehensive approach to sensitive data discovery and classification, it enhances the accuracy and efficiency of data discovery processes. 

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FAQs

1. What is unstructured data?

Unstructured data refers to information that lacks a specific, predefined model, making it difficult to handle using traditional database systems. It includes diverse formats like text files, emails, social media content, videos, and images. The challenge with unstructured data is managing it and extracting meaningful insights due to its varying forms and the need for more standardization.

2. Types of sensitive data found in unstructured data

Sensitive data within unstructured formats encompasses various categories. It includes Personal Identifiable Information (PII), Protected Health Information (PHI), financial details, intellectual property, legal information, and biometric data. These data types are crucial for maintaining privacy and meeting regulatory compliance.

3. Examples of unstructured data Discovery in SaaS

Unstructured data discovery in SaaS involves tools and methods for identifying and managing data across cloud platforms. Techniques include data classification and indexing with AI, and platforms like Strac that use AI analytics for discovering sensitive data within files and emails. Additionally, such solutions automate the discovery, classification, and protection of data, enhancing compliance and preventing unauthorized access.