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Knowing where all your data resides is like playing a game of hide and seek with no boundaries or rules.
Data is ubiquitous, residing in both structured databases and unstructured formats such as emails, documents, and social media posts. The prevalence of SaaS, cloud, remote work, and IoT only exacerbate the challenge of locating confidential data.
Modern cloud solutions and pervasive network connectivity have democratized sharing and collaboration, as enterprises manage millions of documents and dozens of databases every day. Much of this data contains personally identifiable information (PII), financial information, intellectual property and other sensitive information that’s hard to find and protect.
Many organizations look to trusted guides for direction to mitigate data discovery and classification challenges. The Gartner Hype Cycle is a renowned tool that provides insights into the maturity and adoption of specific technologies. By understanding where a technology sits on the Hype Cycle, organizations can make informed decisions about when to invest, wait, and explore alternatives.
For data discovery and data classification, the Gartner Hype Cycle can steer organizations towards the most promising technologies and strategies. It helps them understand the current state of data discovery and classification solutions, their potential benefits, and the challenges they may face in implementing them.
In this article, we’ll focus specifically on the Data Discovery (page 49) and Data Classification (page 66) sections of Gartner’s 2024 Hype Cycle for Backup and Data Protection Technologies.
Organizations must identify what data they have, where it’s located, and how it’s being used. This data discovery process is as critical to an organization’s survival and success as a detailed map would be to an explorer.
Imagine being out in the woods without a map, compass or GPS. You’re likely to get lost, miss important landmarks, and struggle to reach your destination. Without data discovery, organizations are essentially lost — they can lose track of valuable data, overlook potential risks, and struggle to make informed decisions. Data discovery provides the map and compass and guides organizations through their data landscape.
But discovering the data is only the beginning. If data isn’t labeled (classified) correctly, how do you know what data is sensitive and what can be more public?
Data classification is one of the most critical steps in helping organizations identify high-value data by categorizing it into an agreed set of specific and meaningful categories.
Data classification presents numerous challenges, including the diversity of data types, the volume of data, and the dynamic nature of data usage.
The key challenge is taking all the data an entity cares about and classifying it appropriately so that as the data moves through your network, the treatment of the data is consistent — no matter where it is.
Then, you can put the appropriate set of access control rules around it.
With classification, you will have some gradation and taxonomy that dictates how you want your data treated.
Data discovery is a crucial aspect of data management and security. It involves finding, analyzing, and classifying structured and unstructured data to generate actionable outcomes for security enforcement and data lifecycle management.
Data discovery is essential for organizations to manage the ever-growing repositories of data across various infrastructures — including on-premises, hybrid, and cloud environments.
Data discovery is important because it enhances visibility into disparate and unorganized sources of information. The process empowers compliance teams to gain better insight into policy adherence and sensitive information, including personal data. For security teams, data discovery improves visibility into sources containing data access risk.
Gartner recommends using data discovery tools to enhance various organizational functions such as IT, security, privacy, compliance, and business operations. They also recommend leveraging data discovery insights to understand data risks, determine data location and access, improve data lifecycle management and facilitate data classification and analysis to inform business decisions.
Gartner’s analysis shows that data discovery has a moderate benefit rating and is in the early mainstream stage of maturity, with a market penetration of 5% to 20% — demonstrating an increasing awareness of its value in managing and securing data.
Data classification plays an equally key role in data management and security. When structured and unstructured data is categorized into specific groups and labels, you can generate actionable outcomes for security enforcement, regulatory compliance, and data lifecycle management.
For compliance teams, data classification provides a clear understanding of data privacy requirements and adherence. For security teams, it improves risk management by highlighting high-value and sensitive data that require strict protection measures.
Gartner recommends fostering collaboration between security and risk management leaders and chief data and analytics officers to architect and use classification, with a focus on applying consistent classification policies to identify, tag, and store organizational data. Implementing data classification with user training as part of a data governance program is crucial.
Organizations should also document classification use cases and efforts, keeping relevant stakeholders informed. Combining security classification with efforts to adhere to privacy regulations is essential, whether data is classified by nature (e.g., PII, PHI, PCI information) or by type (e.g., contract, health record, invoice). Data records should also be classified by purpose (e.g., data subject request) or risk category to indicate associated confidentiality, integrity, and availability. Automating the classification and labelling of data objects wherever possible is critical, especially considering the scale at which the average enterprise produces data.
Gartner’s analysis shows that data classification has a high benefit rating and is already at mature mainstream adoption.
Concentric AI is a recognized vendor in Gartner’s Hype Cycle for Data Discovery and Data Classification. Concentric AI uses advanced machine learning technologies to autonomously scan, categorize, and classify data. This includes everything from financial data to personally identifiable information (PII), intellectual property, and business confidential information. Our solution works across all types of data repositories, whether on-premises, in the cloud, in structured or unstructured data stores.
It’s important to reiterate the key challenge: knowing where your business-critical data is and understanding what types of data you have. As organizations increasingly embrace cloud transformation, data can easily be shared, copied, duplicated, modified, and shared again. This only exacerbates the data classification challenges.
Concentric AI’s solution gives organizations the confidence they need. It provides a clear view of where sensitive data is located, all with semantic context for a better understanding of risk.
Concentric AI eliminates the issues of inaccurate data classification, unmarked data, complex rule sets, and end-user frustration that are common with traditional data discovery methods.
Concentric AI Semantic Intelligence also seamlessly integrates with all the leading frameworks, including Microsoft’s Information Protection (MIP) solution for data classification and management.
Concentric AI’s data discovery solution offers a comprehensive, machine learning-based approach to data discovery and classification. It provides organizations with the tools they need to manage their data effectively, reduce risks, and comply with regulatory requirements.
As the data landscape readily evolves, data discovery and data classification solutions are no longer a nice-to-have; they’re table stakes for all types of organizations and industries. If you don’t know where your data is and what type of data you’re storing and processing, how can you keep it secure or comply with regulations?
As Gartner’s Hype Cycle and market analysis suggest, data discovery and classification are more than just trends.
Want to see firsthand — with your own data — how you can quickly and easily deploy Concentric AI to discover and classify your data without rules, regex, or end-user involvement?
Book a demo today.
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