In recent years, the field of research and business applications in the field of obtaining, archiving, analyzing and processing data in Big Data database systems has been developing strongly.
In many companies, especially in large corporations, integrated risk management systems are built and improved.
Integrated risk management systems combine risk management processes in various areas of a company, institution or other organization.
One of the areas of risk management, the importance of which in many companies is growing, is risk management in the area of obtaining, archiving, analyzing and processing data in Big Data database systems.
In view of the above, I am asking you: Are the risk management instruments and models for the acquisition, archiving, analysis and processing of data in Big Data systems already being developed? Are you already familiar with examples of this type of systems with risk management risk, which concern the acquisition, archiving, analysis and processing of data in Big Data systems? Please reply
The issues of the use of information contained in Big Data database systems for the purposes of conducting Business Intelligence analyzes are described in the publications:
https://www.researchgate.net/publication/323244120_The_Big_Data_technologies_as_an_important_factor_of_electronic_data_processing_and_the_development_of_computerized_analytical_platforms_Business_Intelligence
https://www.researchgate.net/publication/327035102_The_Technological_Solutions_Big_Data_and_the_Importance_of_Business_Analysis_According_to_the_Business_Intelligence_Formula
I invite you to discussion and cooperation. Greetings
Hi Dariusz,
https://bit.ly/2PfxooY, propose some interesting model which i believe is relevant. https://bit.ly/2yWvTSg can be considered as well.
The issues of the use of information contained in Big Data database systems for the purposes of conducting Business Intelligence analyzes are described in the publications:
https://www.researchgate.net/publication/323244120_The_Big_Data_technologies_as_an_important_factor_of_electronic_data_processing_and_the_development_of_computerized_analytical_platforms_Business_Intelligence
https://www.researchgate.net/publication/327035102_The_Technological_Solutions_Big_Data_and_the_Importance_of_Business_Analysis_According_to_the_Business_Intelligence_Formula
I invite you to discussion and cooperation. Greetings
If I understand you correctly, you are asking about risk management tools used in the field of Big Data analytics. In practice, I can see two main aspects of this.
There exists technical protocols and best practices to ensure information security. These are ensured both physically and logically. For an example, we follow the SOC-2 standards, which is audited once a year by a third party evaluation and certification body.
There are automated intrusion detection systems to periodically test information systems for security weak-points. These alerts the administrators about possible security loopholes before a hacker would discover them.
Before a software is released for production, there are several layers of thorough testing both automated and manual to verify the functional integrity as well as security. Software are released for production environment only after passing these simulations in a separate virtual environment.
Sometimes, data in a Big Data information system is not all contained in a single Database, but spans across multiple storage systems and servers. All these storages of information require both storage level encryption and access control.
Access control is another aspect of information security risk management. Nowadays many information systems offload user authentication into third-party authentication providers. This is implemented as Single Sign On [SSO].
Software agents processing data in large enterprise applications also have an identity, called a service account. These are also authenticated and authorized to access various services for information.
Information can be encrypted in storage level for most data storage mechanisms. While in transit, data can be encrypted using Transport Layer Security [TLS].
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