When we refer to data and files we refer to the concept of heterogeneous information, which can come from traditional relational databases and other sources, as a Hadoop storage system., Let's say.
In these cases, different origin can be a hindrance that prevents a correct implementation of the integration policy. Not in vain, integrating Hadoop is challenging that can't always be overcome. Repeatedly it is a consequence of the same technological difficulty.
File and data management security
At the same time, continuing with the example, Hadoop itself will require extra effort to protect the data, since there are no safety standards, within a comprehensive security design, covering all data and files. At the same time, must be adapted to different needs and, In general, different data protection systems are used (CPD systems, data masking, etc.).
To that end, apart from this example, secure file and data management requires the ETL processes run in favor of better management, entendida tanto desde el punto de vista de la seguridad como de una mayor accesibilidad y capacidad analyticsAnalytics refers to the process of collecting, Measure and analyze data to gain valuable insights that facilitate decision-making. In various fields, like business, Health and sport, Analytics Can Identify Patterns and Trends, Optimize processes and improve results. The use of advanced tools and statistical techniques is essential to transform data into applicable and strategic knowledge...., among other advantages.
Integration, key to safe and efficient administration
The keys to secure file and data management in an organization, thus, will be associated with the processes of data integration, that improve the security of all types of information by reinforcing the following aspects:
-
Minimize the risks of attacks.
-
Greater efficiency in handling.
-
Information is not lost.
Data protection is essential to be able to treat them properly and obtain value from them. One more time, We refer to data governance as a key concept so that greater efficiency and lower risk translate into business intelligence that gives data a strategic value..
Security best practices for data integration
Since companies use cloud-based systems, both public and private, There are some emerging best practices around security that those who implement data integration they must understand:
- Identity and access management (IAM): In this days, most systems, both in the cloud and outside the cloud, are complex distributed systems. That means IAM is clearly the best security model and best practices to follow with the emerging use of cloud computing.. The concept is simple; Provide a technology and security approach that enables the right people to access the right resources, at the right time and for the right reasons. The concept follows the principle that everyone has an identity. This includes people, servers, API, Applications, data, etc. Once verification occurs, it is just a matter of establishing which identities can enter other identities and creating policies that define the limits of that link.
- Work with your data integration provider to identify the solutions that work best with your technology: Most data integration solutions address security in one way or another. Understanding those solutions is essential to protecting data both at rest and in motion..
- Monitoring and governance: Many of the problems associated with the increasing number of breaches exist due to the inability of system administrators to detect and stop attacks.. Creative approaches to monitoring system and network utilization, as well as access to data, enable IT workers to detect most attacks and correct problems before they occur. As usual, there is a growing number of attempted rape that, as a last resort, lead to a complete violation.
Image source Sscreations / FreeDigitalPhotos.net
Related Post:
