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Data Fabric

Finworks Data Scheduling

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Data Scheduling

What is Data Scheduling?

Due to the dynamic nature of cloud systems, effective job scheduling is very difficult. Multiple strategies have been suggested to improve how jobs in these frameworks are submitted, processed, scheduled, and retrieved (in the event of errors). The data schedulers will monitor data location and then allocate tasks to places where the data already exists or where there is enough available network capacity for transferring the data. 

Finworks data scheduling system was created to achieve several goals, such as reducing overall computation time and increasing resource usage in a near-optimal way. It takes several important factors, such as data location, resource burden, energy consumption, task quality, job deadline, and so on. 

Finworks data scheduling helps organisations; 

  • Allows for the effective and timely distribution of data to appropriate users
  • Reduces the need for human intervention by automating operations
  • Allows users to examine changes in data in real-time

More Resources about Data Fabric

The Importance of Scheduling in a Data Management Solution

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We have found that big data operations have become increasingly reliant on scheduling functionality to enable a variety of useful features, including data ingestion optimisation, data quality monitoring, data transformation, and a variety of other useful functions.

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