Reduce Operating Expenses
 

Operating expenses associated with the ongoing data management required in support of file based workflows can be reduced in the following areas via DataFrameworks:

  • Ongoing operating costs associated with storing, archiving unnecessary data (should not be on file systems), these costs can carry forward for years.
  • Operating costs associated with manual storage clean up
  • Operating costs savings associated with the automation of routine manual data management tasks.
  • Cost reductions associated with reducing the required operator skill set and training
 
 

Actual Customer Example of Costs Associated With Storage Cleanup
 
A complete file system analysis confirmed the operational difficulties associated with reclaiming the use of storage resources. Key metrics are difficult (if not impossible) to gather with standard file manager tools, across multiple heterogeneous file systems. Without such tools, companies are faced with developing custom developed scripts that traverse the file systems then populate spreadsheets for further analysis. However, this common practice of spreadsheet analysis breaks down at such large file counts and requires manual repetition to re-analyze.

The file system analysis for the particular customer identified a potentially significant operational area of improvement (with appropriate tools, visibility, and policies). A combination of project-based structure automation, reporting, and inter-departmental policies drastically reduce the cleanup costs, which were determined to over 155 hours/month and would inevitably grow with increased workflow.
 analysis results analysis results

Critically, batch cleanup requires significant overhead compared to active data management. The yellow zone in the storage utilization graph was required as a buffer to prevent storage starvation. 		<click here for large image>
 
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