Over the years, enterprises have been using big data analytics to enhance their employee performance, make better decisions, and identify better business opportunities. This exhaustive data consumption leads to various big data security and privacy challenges.
Let’s take a look at these challenges.
Most businesses rely on the available big data frameworks in the market that distribute data processing tasks across many systems for their faster analysis of crucial data. Indeed, this reduces the workload but ultimately results in user privacy and security issues.
These databases focus more on flexibility and scalability in comparison to other traditional and relational alternatives. As performance is favored over security, such databases need a high-end environment backed by potential security measures.
There’s a high possibility that your endpoint devices get manipulated by cybercriminals followed by false data generation and transmission. This creates doubt on the authenticity of such endpoints and hampers enterprise IT security.
Many big data environments rely on data mining tools that identify specific patterns in unstructured data. However, the personal and financial information wrapped within gets exposed to internal/ external digital threats.
Restricting unauthorized access to sensitive data and information like medical records is a practice followed by companies. But sometimes people who don’t have the access. still need to use this information which results in complications as big data-enabled technology solutions are not designed to accomplish granular access.
However, you can easily address and overcome these big data security and privacy challenges by implementing robust security solutions that include Big Data Encryption tools, User Access Control, Intrusion Detection & Prevention system, Centralized Key Management, Fraud Detection technologies, etc.
You can also choose our Enterprise Mobility Services to advance your existing system and minimize the associated IT risk.
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