Big Data, D-Generation, Data mining, data vs. information, information vs. knowledge, Internet of Things, n vs. knowledge, Tableau, technology, transportation
The generation to follow the Millennials have been playfully named the D-Generation in which ‘D’ stands for ‘Device’. These kids will grow up expecting their possessions to report back to them on a regular basis. They will not need to take so many hours of drivers education because their cars will be like little miniature buses that drive themselves from point to point along one of three chosen paths from Google maps. The “D-Generates” will probably be unemployed – machines will be doing many of their summer jobs, like taking orders, building widgets, and driving crabby passengers to and from their destination.
Currently, there are more active IP addresses than there are humans on the planet. This is expected to grow rapidly, so that within five years, there will be 50-billion or more active nodes on the net, only a tiny fraction of which are reserved for a human like me. By the end of the 21st century, provided there is no cataclysmic disruption to the energy supply, the internet will essentially be a network of devices talking to one another, and we will be guests on their network.
These machines generate data – so much data, in fact, that the traditional methods of searching through data no longer work. The “signal to noise ratio” is approaching zero. And yet within that sea of noise is sunken treasure. The great discoveries of tomorrow will no doubt take place in the server farms on earth, not in far off outer space.
Doctors are already analyzing data from little wristbands connected to smartphones to see if they can predict when a heart attack will occur. Once they know what to look for, they can advise their patients to come in and be treated for a heart attack that will happen some time the following week. Hopefully they will have an appointment available.
One key to preventing data from becoming noise is to provide metadata. In the world of devices, metadata provides noise with a first and last name. Noise becomes searchable because it is tagged with the information that distinguishes it from the crowd.
Data is nothing until it becomes “information.” Information is vital, but it is nothing until it is analyzed, at which point it becomes knowledge. With machines spewing out data and metadata at an alarming rate, there is already a need for meta-metadata. This is information about information.
It reminds me of that horrible reference book I had to use to do research in the dark ages called “The Reader’s Guide to Periodical Literature.” This was analog metadata. Within the volumes, there was also an index – this was meta-metadata. And the legend that told me what all the indecipherable symbols represented, i.e. Mmlle = “Mademoiselle Magazine” – that was something that may yet need to be invented.
Tableau and other big data software are the closest thing out there to the “Legend” in my analog example. They take data and metadata and convert it instantly into graphs, charts, maps and other helpful tools for visualizing the data. They allow you to identify noise and exclude it from the example. Outliers appear visually, and can be instantly drilled into to see what they are and why they exist.
The big data analysis tools help get us from noise to knowledge quickly. These are the covered wagons that will take us to the next frontier of knowledge. Let’s hope the ‘D-Generates’ are not so coddled by their toasters and coffee machines that they grow idle and choose to ignore the vast wealth of bits and bytes that may yet reveal truths never before known.