Security Data Fabric: An Emerging Solution to Unify Your Cybersecurity Data
Ways to manage data are evolving. One of the emerging solutions is adopting data fabric as a unifying integrated layer. When data is stored in many places at the same time there can be overlooked security vulnerabilities that cybercriminals can exploit. An interconnected data system allows for clear, complete visibility and destroys data silos.
Investing in data is big for organizations because it helps them make informed decisions. It is expensive and complicated because there are many steps to the process (collect, store, analyze, protect, track). With the amount businesses invest into processing data, there are still steps to take to fully tap into its potential.
Some factors that hold businesses back from putting all of their data to use:
Data is stored in a disjointed way where there is no unified system for accessing and using data.
Data is stored in different formats and comes from varied sources making it difficult to formulate connections.
Data privacy regulations and governance require integrating data protections across the enterprise. This is an arduous process that delays access to the data.
Digital transformation and innovation generate data quicker than it is able to be processed and protected.
Constant implementation of new data architectures with silos and more complexity in data governance and storage.
Security Data Fabric is an automated solution for end-to-end data integration. It can integrate governance, enhance security, and give employees streamlined access to data. Data Fabric provides a more coherent way to look at data which can lead to more informed insights.
Data fabric is a concept for data design. It aspires to form connections between processes of resources and endpoints that are usually otherwise viewed separately. With these connections, data fabric can continuously analyze resources and endpoints to feed into the creation and use of universal reusable data that can be applied to all environments despite their vast diversity and quirks. Human and machine faculties are used in tandem to connect data that would otherwise remain distinctly independent and unrelated.
Security Data Fabric is versatile and can benefit an organization's cybersecurity in instances like risk models, fraud detection, and cybersecurity management.
Attributes
Intelligent Data Integration, Accessibility, Protection
Using AI, metadata management, knowledge graphs, and machine learning, management is easier. Automation saves time and resources, data integration eliminates siloed data, and centralized data governance builds and reveals more opportunities for data use cases. Centralized data fabric systems also improve access to data. Bottlenecks from data permissions control issues are reduced because of the centralized location. Granting data access is simpler. With data fabric, security posture is enhanced with improved data privacy controls. Data governance and security are strengthened by a unified data fabric. There is easier access to data and encryption/data masking processes are refined for a more straightforward approach.
Cybersecurity
Data fabric’s centralized nature is clearly intentional but it does have some drawbacks. Centralized data can be a worrisome architecture because attackers have a potentially easier path to access all data, all at once. But with responsible built in defense strategies, data fabric can actually improve data protection. This means that data fabric integration needs to come with integrated security controls.
Process
To start implementing data fabric, it's important to know the location of all existing data. Ater this, all sources need to be connected (custom coding is no longer necessary). For a successful, single, and consistent data management framework, a common playbook is crucial. This playbook can give guidance and conduct all users on how to interact with the new system. Additionally, approach the transition with a detailed plan of action. Be sure to include your security and business teams and gather input from all of the stakeholders as well.
Data Mesh
Mismanaging data fabric architecture is dangerous: data fabric could limit, or remove, historical records of data transactions. This is something to consider before deciding to use data fabric architecture.
Data mesh is an alternative option. While data fabric uses AI and automation, data mesh is reliant on the structure of the organization. Through culture, data mesh brings data product uses together. It uses teamwork and clear communication to define and push for specific data needs.
It is possible to combine both data fabric and data mesh. This would result in automation with a strategic security approach. Through organizational structure, data mesh can define data security needs which can further focus the objectives of the data fabric.
The specifics of the organization's risk tolerance and business operation needs are defining factors in deciding which architecture fits best.
Summary
Security Data Fabric is an emerging solution to the complex challenges of data management. It offers a unified, integrated layer that enhances security, streamlines access, and fosters better decision-making through improved data insights. However, it's important to implement data fabric thoughtfully, with a clear plan that involves security and business teams.
Ultimately, the successful implementation of data fabric can lead to significant benefits, including a substantial reduction in the financial impact of data breaches.
