“Big data” is a relative term in that at least for the past 25-30 years, with the advances in digital technologies, the collected data would look “big” relative to say, a year ago. However, we are currently at a point where the rate of growth looks far more than ever before. According to Wikipedia “Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process using traditional data processing applications.” I believe that all along, we have been keen to collect as much of the data as possible and worry about processing and analysing them later. The act of collecting data has gotten so easy these days that no one wants to get rid of any of these data with the hope that the data will be useful in some fashion, some day!
On the one hand, the availability of such vast quantities of data is very exciting for researchers. On the other there are many issues about analyzing and processing them that need to be sorted out. And then, we need to worry about a whole slew of associated secondary issues such as the misuse of data, long term storage of the data and the impact on the society because of misinterpretation of the data.
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We had a few things that contributed to difficulties during the first week of classes. Our last minute communication to the faculty regarding a welcome change in the time time it took them to login to a Mac in the classroom got us in trouble with some faculty. They felt that such last minute emails create a lot of confusion and concern. I agree that we could have worded it differently by starting the communication with something like “This is about an improvement to the login procedure in classrooms. However, the method you have always used will continue to work. If you are not interested in learning about the new method, you don’t have to read further.” Then a network outage on Friday afternoon disrupted activities on campus and access to the campus resources. Though we have a second connectivity through a different provider, as luck would have it, one of their equipment failed too!
After they came back up, we started seeing weird behaviors – on campus users not being able to get to media heavy resources such as Kaltura or YouTube, and Comcast customers from Massachusetts and New Hampshire were unable to get to the campus resources. Long story short, there were lot of fingerpointing between the ISPs on the actual cause of this and finally, we restored service on Saturday afternoon by clearing routing tables that were found to be corrupt, presumably from all these things going down and passing confusing information back to us.
Now that we are back on line, I thought I would write a bit about the technology “Hype Cycle“, a term coined by Gartner, a well-regarded technology research firm. As you see in the Wikipedia article, the Hype Cycle consists of five phases.
| No. |
Phase |
Description |
| 1 |
Technology Trigger |
A potential technology breakthrough kicks things off. Early proof-of-concept stories and media interest trigger significant publicity. Often no usable products exist and commercial viability is unproven. |
| 2 |
Peak of Inflated Expectations |
Early publicity produces a number of success stories—often accompanied by scores of failures. Some companies take action; many do not. |
| 3 |
Trough of Disillusionment |
Interest wanes as experiments and implementations fail to deliver. Producers of the technology shake out or fail. Investments continue only if the surviving providers improve their products to the satisfaction of early adopters. |
| 4 |
Slope of Enlightenment |
More instances of how the technology can benefit the enterprise start to crystallize and become more widely understood. Second- and third-generation products appear from technology providers. More enterprises fund pilots; conservative companies remain cautious. |
| 5 |
Plateau of Productivity |
Mainstream adoption starts to take off. Criteria for assessing provider viability are more clearly defined. The technology’s broad market applicability and relevance are clearly paying off. |
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