There are constant risks to data ever since the world became aware of hackers. Universities and such large educational institutions are the favorite targets of hackers who spin private data and exploit them for their fancy. Generally higher educational institutions have not been keeping tight security protocols for voluminous data and most often there have been accidental data loss and exposure. The volume of personal data collected by universities and other educational institutions coupled with unsavvy population has been the culprit in most cases.
Some ways by which data is breached are listed below
Privacy/Security: The biggest risk anyone involved in large amount of data faces is privacy/security. Privacy, in the world of big data indicates any or all identifiable information blocks that may be used to establish an individual’s identity. The problems concerning privacy in big data applications are-
- What types of personal data can be shared and with whom
- Whether communication through internet can be transmitted confidentially
- Whether anonymous communication is possible, if yes, how.
Storage, further, has different options based on the modern technology as against the regular hard drives. Depending upon the volumes that are to be stored and on the type of data usage there are novel methods of storage which can be utilized.
Cyber security and data privacy
Large volumes of data evoke “false confidence” in the predictive capacity of data analysts.
Results from Big data analytics are vulnerable. They can be easily manipulated, misinterpreted, or misused by individuals or organizations to present cases in their favor.
Too much dependence on data can also be risky. There are many factors outside data which are as critical as data. Some of them are strategic goals, trust, respect, instinct etc. The real concern in big data analytics should be to have a thorough understanding of the data which is being used to gather insights. Big data help in some ways, but they are not without limitations. If security measures become liberal the result would be disastrous. Large amounts of data help in decision making by providing all the necessary information in time. A deep understanding of the circumstance and context is very much necessary in order to gain positive results. Bulks of data cannot solve all types of problems in business. They fit in well in scalable and variable data environments. A friendly association among various networks would be required to solve different types of business problems.
Many organizations have chalked out risk management schemes especially banks have Enterprise Risk Management (ERM). Though this facility underestimates the importance of data it deals with timely scrutiny and proactive management of risk across business. A sound ERM framework would include the ability to monitor in near real-time and it will have an impact on lending and trading decisions in the bank sector. But any deficiency in the data volume will hamper the success of ERM. When poor data is combined with the management of risk, the ERM will be undermined.
When big volumes of data are involved the immediate concern should be to have tight security measures. Profile and personal data must be confidential. Security breaches are highly probable in cyber activity; therefore, no room should be left for hackers and breaches. Educational institutions and other organizations should have personal log in facility which would minimize the risk to a great extent. Usernames and passwords should not be disclosed to anyone at any cost. Volumes of data cannot be totally avoided, but they should be kept safe from security attacks.
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