Shelf Life of Data Research Papers (original) (raw)
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Exponentially growing data, big data, dark data and data trash are throwing excellent opportunities in the world. But associated costs and risks are also significant. “Big Garbage in, Big Garbage out” seems new phrase in computing. This... more
Exponentially growing data, big data, dark data and data trash are throwing excellent opportunities in the world. But associated costs and risks are also significant. “Big Garbage in, Big Garbage out” seems new phrase in computing. This paper is motivated by risk and cost stresses on non-IT firms. Literature review, from management perspective, reveals lack of world’s attention towards immortality of data in the data stores of the world and rising risks & costs. Progressive digitization calls for regular elimination of data trash and consequent avoidable costs. Existing concept of Time to Live (TTL) or hop limit is eliminating huge data in transit on the internet system in real time. Similar concepts and tools could be potential help in reduction of size of data inventory. Paper presents a rudimentary model for expansion of concept of TTL with the assistance of user defined shelf life of data.
Exponentially growing data, big data, dark data and data trash are throwing excellent opportunities in the world. But associated costs and risks are also significant. “Big Garbage in, Big Garbage out” seems new phrase in computing. This... more
Exponentially growing data, big data, dark data and data trash are throwing
excellent opportunities in the world. But associated costs and risks are also significant.
“Big Garbage in, Big Garbage out” seems new phrase in computing. This paper is
motivated by risk and cost stresses on non-IT firms. Literature review, from
management perspective, reveals lack of world’s attention towards immortality of data
in the data stores of the world and rising risks & costs. Progressive digitization calls
for regular elimination of data trash and consequent avoidable costs. Existing concept
of Time to Live (TTL) or hop limit is eliminating huge data in transit on the internet
system in real time. Similar concepts and tools could be potential help in reduction of
size of data inventory. Paper presents a rudimentary model for expansion of concept of
TTL with the assistance of user defined shelf life of data