Unlocking The Full Potential of Enterprise Data
• This approach can introduce major security risks as new systems tend to be more secure .
A better strategy is to gradually migrate eligible data assets to other systems after their transactional lifecycle track has ended . However , this raises several important observations and questions :
• Can lifecycle policy enforcement processes transcend individual systems and be applied consistently across systems ?
• The majority of transactional and operational systems cannot act as Systems of Records 33 , therefore the migration of valuable data may be a necessity .
• To ensure the integrity of the lifecycle management process , it is essential to carefully consider which contextual metadata should be migrated with the data asset .
3.7 COST JUSTIFICATION
Managing the lifecycle of enterprise data presents significant cost-justification challenges , particularly if it is done at a granular level . Recognizing this challenge some two decades ago , US NARA recommended a " big bucket " approach that broadened the scope of data and record types and significantly reduced their numbers . This method has since been adopted by many global corporations .
Despite this , the plummeting costs of on-prem and cloud storage have made it increasingly difficult to justify data lifecycle management programs based on complex operational , business , legal and compliance requirements . So organizations are tempted to base their enterprise data lifecycle management programs on pragmatic IT cost considerations alone .
The reality is that the loaded costs of owning and managing valuable enterprise data far exceeds direct storage costs . This includes the cost of disaster recovery systems , IT staff , IT physical infrastructure , energy , security , etc ., all of which are rising . Additionally , keeping valuable data in “ hot ” silos beyond its operational lifecycle burdens IT and OT infrastructure ( edge , digital twins , IoT endpoints , etc .), complicates data retrieval and application decommissioning , and challenges disaster recovery . It also hampers compliance and litigation responses . Effective data lifecycle management programs grounded in operational , business , legal and compliance defensibility considerations function as macro filters that enhance the tangible and intangible value of data . In contrast , moving unfiltered data to the cloud results in a growing mess .
Assigning precise cost figures to the above depends on organizational specifics , including its data growth volumetrics , its IT and OT infrastructure , business domains and jurisdictions regulations . The annual cost of owning and managing valuable data can be anywhere from a few thousand
33 https :// en . wikipedia . org / wiki / System _ of _ record Journal of Innovation 47