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Writing data is when you store it. Reading data is when you retrieve what is already stored.This is really not much different than understanding the difference between writing something onto paper and reading something off of a piece of paper.
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∙ 9y ago
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What is the difference-between reading and writing a disk?
Reading a disk involves accessing and retrieving data that is already stored on the disk, while writing to a disk involves adding new data or modifying existing data on the disk. Reading does not change the content of the disk, whereas writing alters the information stored on the disk.
What kind of access refers to reading or writing data consecutively?
That would be sequential reading or writing, as appropriate.
What is the act of reading data from or writing data to a storage device?
access
What tools allows you to check the surface of a disk to see if the sectors are capable of correctly reading and writing data?
surface of a disk to see if the sectors are capable of correctly reading and writing data
What is the process of transferring data instructions and information from a storage medium into memory?
reading
What is the difference between OLAP and data mining?
difference between Data Mining and OLAP
............. refers to reading and writing data consecutively?
sequential access
What is the difference between allocation and search data structure?
difference between serch data structure and allocation data structure
What is the difference between data communication and data communication information2010to2013?
The scope of work and the educational requirements are the difference between data communication and data communication information.
What is the difference between primary data and secondary data Don't make it complicated please?
The difference between primary data and secondary data is that primary data is the information from the original research.
What UNIX file that contains instructions for performing a specific task such as reading data from and writing data to a hard drive?
kernel module
What is the difference between a model-driven and data-driven DSS?
A model-driven DSS relies on mathematical or statistical models to analyze data and make predictions, while a data-driven DSS uses historical and real-time data to generate insights and support decision-making without relying heavily on predefined models. Model-driven DSS are more structured and use algorithms to process data, while data-driven DSS focus on exploring patterns and trends in data to inform decisions.
