Get end-to-end data governance and security enforced uniformly at all layers of the stack to manage data lineage, auditing, quality rules, quality monitoring, security, retention, and archiving.
Don’t leave data security to your application developers. Secure your data at the platform level and govern it throughout its lifecycle.
Ensure the highest levels of protection for your data, rapidly implement data policies, and apply end-to-end governance.
Process content and extract information using model-generated rules, NLP, ML, and fact extraction to get the best of both worlds—precise and consistent results with the ease of automation.
Data reliability, security, availability, and scalability from a single, enterprise-grade data management platform.
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Data loss prevention and other security principles are central to the MarkLogic data platform. Network and application security is important, but at MarkLogic, we’re driven by the principle that data must be secured at its core where it resides in the database. That’s why large investment banks, major healthcare organizations, and classified government systems all trust MarkLogic with their most critical data assets.
Leverage document fingerprinting to intelligently identify and secure assets that might contain sensitive information or trade secrets.
Leverage pre-built models and classification standards to enforce governance best practices.
Use automatic or assisted classification and apply appropriate retention policies to save time and costs associated with storage and processing.
Classification tools provide a transparent and complete audit trail of the compliance checking process.
Protecting your most critical data is our specialty. World-class enterprises and government agencies around the world trust MarkLogic to handle their mission-critical data with industry-leading, unparalleled security as verified by Common Criteria Certification.
Protect your data in transit and at rest with comprehensive, transparent, and fast encryption.
Govern what users can do or see with granular access controls based on role, collection, document, element or property.
Leverage built-in functions for concealing, masking, patterns, and custom rules, and combine with policies to match any target need.
Keep track of when an event occurred (the valid time), as well as when the information was added (the system time) to fully recreate any truth—no matter how long gone—as it was at any given moment.
Improve data quality, enforce governance, and create business value, all from a single platform that provides an alternative to traditional slow and brittle master data management (MDM) tools.
Keep your data and metadata together to tag, classify, manage, deliver, and audit your data from a single, unified platform.
We need to have a sense of unified data available, govern it properly, and apply security to make sure that we can share that knowledge throughout our organization. So, we are utilizing MarkLogic to break away from the silo approach—we have a unified sense of data and can also enforce proper controls over it and empower our employees to access the data.
Senior Enterprise Architect, The Boeing Company Learn more
There’s a whole new way of defining security and what it means to have data ownership. You can have shared infrastructure, and I can define security models in a way where different groups in the organization can have access to their own data, but we still have one copy of the data.
Head of Technology Asset Management, Credit Suisseinvestment bank logoLearn more
Thanks to the MarkLogic advanced security capability, we were able to build a very granular security model that implemented an access control matrix based on security classification and user roles. Within the matrix a user may have three different access levels, from full access, search-only access, to no access at all.
Founding Data Scientist, DuPont Learn more
Data security in data governance deals with the rules and processes to uphold data security. At a broad level, it covers security checks for employees, redaction rules for protecting PII information, encryption and password-protected data requirements and more.It’s important to consider data protection at the database level first. This helps minimize the risk of corruption or unauthorized access later in its lifecycle as data moves between environments and applications.
As a fundamental component of a long-term data strategy that treats data as a strategic asset, data governance plays a crucial role, while data management addresses the operational aspects of executing that strategy. Data management encompasses the technical aspects of managing the full data lifecycle. These include1) data ingestion and storage, 2) integration, harmonization and enrichment, 3) securing and governing, 4) preparation and transformation, 5) retrieval and discovery, 6) secure access and visualization and 7) persistence, such as backup, recovery and archiving. Data governance focuses on establishing organizational policies, frameworks and tools to align data-related requirements with the business strategy. This comprises data accuracy, consistency, regulatory compliance, internal policies, data quality, security, privacy, auditing and risk management. Additionally, data governance involves defining data ownership, roles and responsibilities and enforcing policies and procedures across the organization.
Don’t waste time stitching together components. MarkLogic combines the power of a multi-model database, search, and semantic AI technology in a single platform with mastering, metadata management, government-grade security, and more.