By David SimsYou have got to love a white paper titled “The Toxic Terabyte.” That is, in fact, the title of a classic white paper from IBM (News - Alert) discussing the question of whether data dumping threatens business efficiency (a good topic to be considering when thinking of proper network management.)
(Short answer: Oh yeah.)
Plus you gotta love a paper which realizes that the Industrial Revolution (News - Alert) wasn’t a one-off, but was of a piece with how people still are: “Some observers have likened what is happening to the Industrial Revolution, when economies made the first move away from individual craftsmanship and towards the production line, with its potential for quantum increases in output. Except now it is not pots and pans or cars that are being produced in their thousands, but data bits in their millions, billions and trillions.”
Knowledge is power, the paper avers – but “only if it can be extracted quickly and efficiently from an ever-growing mass of data. Businesses and other organizations now see their information stocks snowballing beyond their ability to manage them and beginning to work against the health of the enterprise by damaging efficiency and bottom lines.”
Or, in other words, the toxic data dump. (Cue minor key, ominous and menacing theme music, up and under briefly.)
The usual answer to the data pile-up is more cheap storage and lots of it – true back in 2006 when the paper was written and even more true today. But reflexively “pumping everything and anything into an apparently limitless reservoir” hurts the organization in three ways, it notes:
“It becomes harder and harder to retrieve information promptly, more people are needed to manage increasingly chaotic data dumps and networks and application performance are slowed by excess traffic.”
The answer? Information lifecycle management. “An important area is Information Lifecycle Management, which can help companies predict storage needs and related costs," suggests Erwin Chuaunsu, country manager for systems and technology group, IBM Philippines.
There’s a more useful explanation in the paper itself – read on if you’re interested.
