Share your thoughts on mainframes and distributed data processing:
- How do data transmission errors affect your perception of each? In other words, does the possibility of error influence your decision regarding which would be better?
- What other factors would affect a company’s choice?
Respond to student’s response below:
The advantages of a mainframe is that all of the organizations data is stored in one central location, this makes maintenance easier as well as allows for more strenuous security protocols and it is not dependent on outside agents for users to gain access to data. These advantages can also be seen as a serious disadvantage in that should the main frame fail all data can be potentially lost, as well as mainframes can be extremely costly and maintenance downtime periods can be hard to schedule in a global corporation.
The pros of distributed data processing are that the data is spread out across multiple systems, and can be coded to pull from the closest geographically to the user, it is also much cheaper when compared to the costs for a mainframe and should one of the data points fail data is not lost and can be restored when the failed data point is brought back on line. One drawback to the this set up is that it is heavily dependent on an internet connection in order to function, if a region suffers a catastrophic failure of the internet the potential of a serious data compromise can occur
I think the driving factor that a company would need to consider if deciding between mainframe or distributed data processing is what their business model is and what is your budget, do they need a more centralized file structure that can be secured like a bank or would a distributed structure be better for those who are working remotely or while traveling making access to central system difficult. Cost would also be a concern.
POSTS
Respond to student’s response below:
The advantages of a mainframe is that all of the organizations data is stored in one central location, this makes maintenance easier as well as allows for more strenuous security protocols and it is not dependent on outside agents for users to gain access to data. These advantages can also be seen as a serious disadvantage in that should the main frame fail all data can be potentially lost, as well as mainframes can be extremely costly and maintenance downtime periods can be hard to schedule in a global corporation.
The pros of distributed data processing are that the data is spread out across multiple systems, and can be coded to pull from the closest geographically to the user, it is also much cheaper when compared to the costs for a mainframe and should one of the data points fail data is not lost and can be restored when the failed data point is brought back on line. One drawback to the this set up is that it is heavily dependent on an internet connection in order to function, if a region suffers a catastrophic failure of the internet the potential of a serious data compromise can occur
I think the driving factor that a company would need to consider if deciding between mainframe or distributed data processing is what their business model is and what is your budget, do they need a more centralized file structure that can be secured like a bank or would a distributed structure be better for those who are working remotely or while traveling making access to central system difficult. Cost would also be a concern.
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