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Organizational data is everywhere: in the cloud, on premises, structured, unstructured… resulting in a significant challenge of finding streams of confidential data. Plus, modern cloud solutions and pervasive network connectivity have democratized sharing and collaboration, with enterprises managing millions of documents and dozens of databases every day. Many contain personally identifiable information (PII), financial information, intellectual property and other sensitive data that’s hard to find and protect.
The challenge
Finding and managing all this data is like exploring the uncharted wilderness. Like an explorer, organizations are constantly on a quest to discover and understand the diverse landscape of their data. They 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 beginning your journey without that map or a compass. You’d likely 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 for this journey, guiding organizations through their data landscape.
A starting point
To mitigate data discovery challenges, many organizations look to trusted guides for direction. The Gartner Hype Cycle is a renowned tool that provides insights about 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, when to wait, and when to explore alternatives.
In the realm of data discovery, the Gartner Hype Cycle can point organizations towards the most promising technologies and strategies. It helps them understand the current state of data discovery solutions, their potential benefits, and the challenges they may face in implementing them.
In this article, we’ll delve into the Data Discovery section of Gartner’s 2023 Hype Cycle for Storage and Data Protection Technologies.
Data discovery is a crucial aspect of data management and security. The process involves finding, analyzing, and classifying both 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.
The importance of data discovery lies in its ability to enhance visibility into disparate and unorganized sources of information. It empowers compliance teams to gain better insight into policy adherence and sensitive information, including personal data. It also allows security teams to improve visibility of sources that may contain data access risk.
Gartner’s analysis shows that data discovery has a moderate benefit rating and is in the adolescent stage of maturity, with a market penetration of 5% to 20% — indicating a growing recognition of its value in managing and securing data.
Concentric AI offers a robust solution to help organizations manage their data more effectively. Concentric Semantic Intelligence 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. The solution works across all types of data repositories, whether they are on-premises, in the cloud, in structured or unstructured dat stores.
One of the key challenges in data discovery is knowing where your business-critical data is and understanding what types of data you have. Concentric AI’s solution gives organizations the confidence they need, providing a clear view of where sensitive data is located and offers semantic context for better understanding. This eliminates the issues of inaccurate data classification, unmarked data, complex rule sets, and end-user frustration that are common with traditional data discovery methods.
Another crucial aspect of data discovery that cannot be overlooked is data classification. As organizations increasingly embrace cloud transformation, data can easily be shared, copied, duplicated, modified, and shared again. This only exacerbates the data classification challenges. With Concentric Semantic Intelligence, security teams can identify sensitive data with semantic context and label data centrally, without the need for complex rule writing or relying on end-users.
Integration with existing classification frameworks is also a crucial part of optimal data classification. Concentric Semantic Intelligence 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 continues to evolve, data discovery 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 is more than just a trend.
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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