For an ever-growing segment of organizations, making sense of unstructured data is quickly becoming a necessity. It is also more difficult. Unlike structured data that is stored in rows and columns, text-based, and easily searchable in relational databases and data warehouses, there is no defined data model with unstructured data. The text is hard to find and includes PDF, images, and video files. Data lives in various forms in applications, data warehouses, and data lakes. Examples of unstructured data include emails, messages, and conversation transcripts.
Forbes reports that unstructured data is growing by 55-65 percent each year, and organizations responsible for it will soon need to secure it to demonstrate regulatory compliance. By connecting unstructured data sources, you can get a reliable inventory of all unstructured data, discover hidden data that could put your organization at risk, and validate and enforce file rights. In this post, we’ll explain the process and approach to tackling the challenge of discovering and characterizing unstructured data. We’ll also tell you how Imperva Data Security Fabric Data Discover and Classify simplifies this process.
Identifying your unstructured data
Most organizations have little insight into what the vast majority of unstructured data files they manage contain or what risk they are exposed to. Many threats from insider mishaps, malicious actors, cyber-attacks, ransomware, and other threats lurk in enterprise environments with files scattered across on-premise and cloud data repositories. Having visibility and creating a framework to profile data is a business imperative for data governance, compliance, security, and privacy. For a large enterprise, the amount of data can be overwhelming, and automated tools are required to help organize it.
There are six key questions every organization should ask to understand their unstructured data:
- Is the data known and managed?
- Where is that?
- What is this?
- What rules apply?
- How is your data managed?
- Who is accessing it?
The first step in the strategy is to establish an enterprise-wide data classification
When you get a reliable inventory of your unstructured data mapped against your security and privacy policies, you can more easily uncover the dark data in your repositories and determine if it can provide value to your organization or put in risk to your organization and to verify and enforce your rights to organizational data.
Note that unstructured data sources are much more diverse than structured data sources, covering hundreds of file types and sources. A consistent, enterprise-wide classification framework should be agentless to allow you to understand both on-premise file servers regardless of data source type and cloud-native data sources like Google Workspace and Office 365. The framework should also provide complete metadata about your data and feature an ElasticSearch index instead of SQL to allow reports in seconds.
Imperva DSF Data Discover and Classify automates the process
Imperva DSF Data Discover and Classify enables you to leverage the automation capabilities of the Imperva Data Security Fabric (DSF) to perform data discovery, discovery, and classification of unstructured data at the level of enterprise, so you can find exposed sensitive data and protect it before auditors or hackers discover it.
Imperva DSF Data Discover and Classify provides visibility into the exact location, volume, and context of sensitive data. Automated, cross-directory searches allow data professionals to perform extensive scans across multiple data source repositories simultaneously – in seconds. It searches for the information required for an auditor’s question, an individual’s data search, or a data deletion request with maximum accuracy at scanning speeds of up to 100,000 words per second.
The Imperva DSF Data Discover and Classify engine analyzes metadata to determine file owner, data type, data category, and other information. It presents these findings to the Imperva Data Security Fabric hub for risk and security analysis. The DSF hub allows users to review large numbers of files for their current access profile, so security teams can ascertain whether any regulated data types may have excessive file entitlements privilege. Imperva DSF has a built-in workflow manager to help automate remediation workflows if action is required. In addition, it can be integrated with other enterprise tools an organization may already be using, such as ServiceNow, improving collaboration among management, compliance, and security teams.
Your organization’s ability to maintain data compliance and meet regulatory obligations depends (or soon will depend) on your ability to discover and sort unstructured data at scale. For example, data compliance with privacy regulations such as GDPR, CCRA, depends on maintaining an accurate inventory of your client, employee, and supplier Personal Data. The GDPR specifically requires that retained Personal Data remain classified, and the regulatory provisions specify that you must implement “state-of-the-art” security measures to protect it. Data protection is central to all compliance regulations that empower regulators to impose fines and penalties for non-compliance in the event of a data breach or breach. Imperva DSF Discover and Classify will help you reduce the risk of non-compliance and the potential for data breaches from an unstructured data source. Classifying data by sensitivity categories such as Restricted, Confidential, Internal-only, or regulatory categories such as PII, Personal, HIPAA, and others, makes it easier for staff to apply appropriate compliance and security controls.
Effective data governance team collaboration on retention and deletion is nearly impossible without a centralized tool to help manage the process. Imperva DSF Data Discover and Classify enables organizations to implement continuous management processes through regularly scheduled data scanning and inventory reporting, simplifying the tracking and management of change.
Unstructured data reporting features provide management professionals with information that can help them collaborate on data management projects to determine which data files are no longer relevant to the business or identify which files contain hidden business value. Obsolete files can be designated for deletion which helps the organization reduce IT infrastructure and maintenance costs.
Another way to strengthen your data management initiatives is to use unstructured data intelligence from a trusted data catalog of a supported platform such as Collibra.
Data discovery and classification is a key compliance and security process. Imperva DSF Data Discover and Classify automates the process so your management, compliance and security staff can manage the process for the unstructured data enterprise as a whole. Imperva DSF Data Discover and Classify helps simplify compliance, save time, save money and protect your organization from the risks of data breaches with sensitive data in unstructured data files. The datasheet explains Imperva DSF Data Discover and Classify in more detail.
Contact Imperva to learn more.
The post How Organizations Make Sense of Millions of Unstructured Data Files at Scale appeared first on Blog.
*** This is a Security Bloggers Network syndicated blog from the Blog written by Bruce Lynch. Read the original post at: https://www.imperva.com/blog/how-organizations-manage-to-understand-millions-of-unstructured-data-files-at-scale/