Stop Manually Collecting Data For Your Data Center!

UofA_2011_825kVA_Delivery_011-001It is critical that any data center have a strong DCIM strategy in place.  Even in relatively small data centers the amount of infrastructure that must be tracked, managed, maintained and more is enough to overwhelm any data center manager.  There are a variety of ways to track and maintain infrastructure but traditionally it has been done manually.  But, is this method truly the most effective way to collect data in a data center?  And, if not, what is the solution?

One way that many data centers have traditionally collected data is to give each piece of infrastructure a barcode.  The barcode can then be scanned and inventoried to keep track of what is where.  But, the problem with this method is that it does not provide much data and the data it does provide is often outdated.  Additionally, it does not provide much insight as to how each piece of equipment within an infrastructure is using energy.  Without that information, how can a data center manager accurately determine where energy is being used appropriately, where it is being underused and where it is being overused?  If an analysis is only completed every 6 months or once per year, that is a lot of time that has been wasted when improvements could have been made, efficiency improved and money saved.  By implementing a more intelligent DCIM management tool it can provide up to data information about equipment and energy consumption so that it can offer real, actionable data that data center managers can use.  Alerts can be arranged based on predetermined thresholds, graphs and charts generated from gathered data and more accurate action can take place.   It is also a far more efficient means of collecting data in a data center rather than manual data collection.  This will save time and many headaches for data center managers, making an improvement any way you look at it.  One of the last and most important reasons to implement an automated data collection method instead of manually collecting data is that it can alert you to potential capacity problems far sooner than manual methods.  Rather than capacity problems sneaking up on data center managers, leading to major problems and the possible expense and frustration of having to relocate, automated DCIM will help data center managers see where capacity stands within a data center far before outgrowth ever becomes a problem so that any necessary condensing, rearranging or cloud storing can take place to save room.  Manual data collection may have been the way thing were done in the past but it is not the way of the future and data centers that make the switch now to automated DCIM will enjoy the variety of benefits it has to offer.

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