signal and the noise a Data Science problem – not very different from our everyday problems?

Data, Big Data, Small Data and Science to find meaning, knowledge nuggets from this massive amount of information is the sexiest job of 21st century according to a leading publication.  Circa 2005, web 2.0 bustling with energy and ideas gets a massive thumbs up from millions and millions of people by joining the bandwagon. As the Social media took center stage by 2007 and Modern mobile devices became a rage, user generated content took center stage. Internet Content created by people dwarfed the Content that was created by centralized entities (corporates, governments and institutes).

Circa 2010, machines joined internet revolution – now the machines (IOT surge would mean the machines will continue to rise in numbers)  that connected to internet outnumbered the people that were online. A new kind of data, content and knowledge is being created. But more importantly, a lot more of data is being created. This led to a new web paradigm – web 3.0 – semantic web, an internet that could contextualise, personalize and filter through the noise and provide people with what they wanted.

Fundamentally, new generation that leaves their valuable data online, with their favorite brands  expects  that this data would be used to create meaningful experiences for them. Experiences, that are personalized to individual needs, contextualized to their environment, and suited to their needs and wants.

Thankfully, the internet giants haven’t been busy just gathering your and mine data but has also been developing technologies and solutions to solve our problems. One such advancement has been through “Big Data” platforms. There has been a surge in new and reinvigorated interest in Databases, Processing technologies, Distributed computing platforms, Data Science and Machine learning algorithms in helping solve the problem of mining the “intelligence” from this massive data that we create and consume on everyday basis.

Data Science helps us find answers, look through the signals to cut out the noise to get to meaningful events, intelligence that could give us beautiful insights, knowledge nuggets about the world, our interactions with the wold an insight into our behaviour that (even) we might be unaware of (consciously). We are at a tipping point in information revolution, now we move from “discovering the intelligence” to “mastering the intelligence”.  You can see the glimpses of that future in science fiction movies – minority report, HER (one of my favorite future prediction).

Have you ever been asked: “What is your passion?” 

I am sure that question has been posed to you at every step of the life – when you were a student, professional or whenever you found life and career started to stagnate. As a student – i had so many things going for me, so many things that excited me and yet i didnt really know what is it that i was passionate about ? what interested me the most? I would think that i am yet to find my passion – not everyone is lucky to find it early enough in life. Interestingly (but not surprisingly), these problems are similar to data problems – we always learn and derive from our life experiences. A student has to rely on his “Data Science” skills to cut the noise – his model of making sense is very different from the model that a professional builds for himself when he is looking for the right Job. But we all are using “Data Science” to walk through a maze – all the time, trying to derive from all that we have gathered (data as experiences) right through our lives.

There are so many examples in dailylife that we play data scientist – a parent goes through barrage of data to select a right school for their kid, we are always analysing our friends behaviour – in fact many a times predicting their reactions to situations. In short we are all always using some form of Maths, Stats and Algorithms to solve our every day lives – but fail to recognise that, in many ways thats a fault in the way we have been or are being taught these subjects (dont want to even start on this).

My humble submission here is that “Data” problem is not for selected few, it is for all of us – like Technology became essential way of life, professional life – data would becomes significantly more important, so we all need to recognize that and make peace with it. Adopt Data and the Data Scientist with in, use it for your advantage.

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