Symptoms of Unstructured Data Problems
 
To help identify problem areas it is necessary to seek out tell-tale symptoms. Some may be obvious but generally ignored, others need the benefit of experience and often tact to uncover. Collectively the symptoms can cause significant inefficiencies resulting in wasted time, unnecessary costs, and poor customer deliverables.
<click here for customer inefficiency comments>
Infrastructure   fingerprint image
 
   
  • Constantly running out of disk space and don't understand why?
  • Routine "emergency storage purchases"
  • Network seems slow (often the result of poor data distribution, and many processors converging on a given partition or file system.)
  • At any given time some file servers and disks are highly active, or at capacity while most are idle or under utilized.
  • Storage, maintenance, and data management increasing as percentage of IT budget.
  • Storage growth disproportionate to business growth (storage capacity growing at 56% per year and business growing at 5%
  
Production Workflows
 
  • Output not completing in a timely fashion (interpretations, renders, compiles, etc.)
  • Companies in a data pipeline crisis often get caught in a vicious cycle of running to fight data related fires and never seem to have time to stop the chaos to actually help themselves improve the situation.
  • User perception "why do we have an IT group, if we need to worry about data... that is their problem. True, but even if you stopped generating data today, IT and Finance will own the ongoing bill for data already generated for many years to come... which then becomes a company / finance problem.
  • Just give us the space, we will manage it... wind up with blocks of data scattered about their playroom. No one is addressing efficiency of data across departments and the organization as a whole. The only choice then becomes to react and buy more storage.
   
Data System  
 
   
  • Difficulty finding data, difficulty finding all data for project, customer, work order.
  • Difficulty determining quality of data
  • People constantly staying late, fighting fires and daily processing to manage output.
  • Difficulty accounting for all data on your systems (why is it there, what project does it belong to, can it be removed, who should we talk to or who is responsible for the data?)
  • Data related schedule delays
  
     
The preceding text highlights some areas in the infrastructure, data system, production workflow, and burgeoning unstructured data that may well harbor one or more apparent or hidden difficulties. Any one of which may have a significant value to the business.