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Meeting these expectations comes at a price to government agencies where it concerns managing information – more specifically, ease of access; data integrity and accuracy; capacity planning to ensure the timely delivery of data to remote (possibly mobile) sites; and managing the security of corporate and public information. [48]
Such data is usually processed using real-time computing although it can also be stored for later or off-line data analysis. Real-time data is not the same as dynamic data. Real-time data can be dynamic (e.g. a variable indicating current location) or static (e.g. a fresh log entry indicating location at a specific time).
Monitoring - keeping track of data quality over time and reporting variations in the quality of data. Software can also auto-correct the variations based on pre-defined business rules. Batch and Real time - Once the data is initially cleansed (batch), companies often want to build the processes into enterprise applications to keep it clean.
Lead Time vs Turnaround Time: Lead Time is the amount of time, defined by the supplier or service provider, that is required to meet a customer request or demand. [5] Lead-time is basically the time gap between the order placed by the customer and the time when the customer get the final delivery, on the other hand the Turnaround Time is in order to get a job done and deliver the output, once ...
However, data has staged a comeback with the popularisation of the term big data, which refers to the collection and analyses of massive sets of data. While big data is a recent phenomenon, the requirement for data to aid decision-making traces back to the early 1970s with the emergence of decision support systems (DSS).
In such systems, failure to deliver the real-time data will adversely affect the performance of the systems, and some systems, e.g. safety-critical, safety-involved, and some secure mission-critical systems, must be proved to perform at some specified minimum level. This, in turn, requires that a specified minimum reliability for the delivery ...
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Data synchronization is the process of establishing consistency between source and target data stores, and the continuous harmonization of the data over time. It is fundamental to a wide variety of applications, including file synchronization and mobile device synchronization.