Introduction
The more significant big data analysis becomes for businesses, the more critical data security. For example, if you work in healthcare, you'll undoubtedly want to employ big data applications to track changes in demographics or patient demands. This information on your constituents must be kept secure to meet regulatory requirements and safeguard the patients' privacy. You'll need to consider who is allowed to see the data and under what conditions they can do so. You'll need to be able to both authenticate and secure the identities of users and patients. These security concerns should be built into the big data fabric from the beginning rather than being an afterthought.
Challenges in Data Security
The requirements of security and privacy of the big data stack are similar to the requirements for other data environments. Specific business needs must be closely matched with data security standards. When big data is used in a plan, it presents certain distinct challenges:
- Data access: The technical requirements for user access to big data are similar to those for non-big data solutions. Only those having a valid business need to examine or interact with the data should have access to it. Most fundamental data storage platforms have stringent data security measures in place and federated identity capabilities that allow for adequate access across the architecture's various layers.
- Application data access: From a technical standpoint, application data access is also pretty simple. Most application programming interfaces (APIs) provide security against unauthorized use or access. For most large data applications, this level of protection is likely sufficient.
- Data encryption is the most challenging part of data security in a large data environment. Encrypting and decrypting data in typical contexts puts a lot of strain on the systems' resources. With extensive data, this challenge is amplified. The most straightforward solution is to increase computational capability. A more moderate method would be to determine the data elements that require this level of security and encrypt only those that are needed.
- Threat detection: The addition of mobile devices and social media sites rapidly increases the amount of data and the potential for security risks. As a result, businesses must take a multiparameter strategy for data security.