Unlocking The Full Potential of Enterprise Data
• Develop classifications for record categories ,
• Establish lifecycle retention policies for these categories ,
• Categorize remaining assets ,
• Enforce the appropriate retention policies on these assets .
The 1990s marked the onset of digitizing and digitalizing front-office and back-office functions , resulting in the generation of massive volumes of electronic records such as documents , emails , transaction reports , and more recently social media data . The lifecycle methodology initially developed for paper records was adapted to manage these new formats . This methodology must be adapted again to suit the new modality of OT data .
3.2 LIFECYCLE TRACKS
The value of data assets , whether tangible or intangible , present or future , encompasses multiple dimensions : transactional value , operational value , business value , legal and compliance value , and archival value . There may be more dimensions to the data value .
Figure 3-1 shows the different lifecycle tracks that are associated with these value dimensions . It also shows a liability track which represents the notion that data assets can become a liability during their lifecycle . Refer to the discussion in section 3.4 for details . The lower part of the diagram indicates that data assets may migrate across multiple systems during their lifecycle . Consequently , the lifecycle policy assigned to the asset must persist through these migrations . Refer to section 3.6 for details .
Figure 3-1 : Lifecycle tracks of enterprise data assets . ( Source : IGnPower )
42 February 2025