Data Science, and Introduction

Microsoft in the News

The pen is mightier than the keyboard.

With the ubiquity of keyboards and the powerhouse force that is voice-to-text, you can be forgiven for thinking that the once mighty pen is on the brink of extinction.  You may still be right, but if it is, we will be the worse for it.

In a peer reviewed paper by Audrey van der Meer and Ruud van der Weel from the Norwegian University of Science and Technology, it has been found that using a pen instead of a keyboard is a better way to learn.  The sensory rich motor experience of writing facilitates learning by activating higher levels of cognitive processing.  The researchers compared the performance of two groups using a Surface Pro 4.  One group used the keyboard while the other used the Surface Pen.

By capturing data through a high-tech hairnet, the researchers were able to conclude that using a pen improves the mind’s ability to both process and retain information.

That back to school laptop may not be the best thing you can do for yourself or your loved ones, unless, the laptop incorporates stylus technology like the Surface Pen.

Data Science, and Introduction

If somehow, back in the year 200 BCE, someone was frozen and then woken up in, perhaps 1000 CE, they would, for the most part, feel quite at home.  Not much would have changed for her during her 1,200 year nap.  I, on the other hand, struggle to keep up with the changes happening just in IT, on a daily or weekly basis.  The speed of change has morphed drastically over the past 100 years, and it is speeding up.

As I try to follow, and sometimes even lead, in this ever-changing landscape, I keep coming back to data.  With the internet combining with the internet of things, data is being produced at an ever-increasing rate.  It was said in 2015 that 90% of all the data in the world was created in the last two years.  I’ve seen that same statistic trotted out in 2017.  If this is true, and the trend continues, perhaps we will pass this threshold again in 2018?

Of course, not all data is created equal.  The data generated by a single peer reviewed scientific paper is miniscule compared to the data generated by a single episode of the TV show Shameless.  The paper, I would argue, has more value, depending on the metric you are using to determine value.  Finding the value in the ocean of data is the job of the data scientist.

This tide of data has given rise to the buzzword, Data Scientist.  In 2001, Data Science was, for the first time, seriously thought of as its own discipline.  At that time, Data Science was thought to combine the fields of statistics with Computer Science, as they pertain to data.  Since this is still a new field of study, if you were to sign up at your local university for a Data Science degree, you would likely experience a unique curriculum since there is still no consensus on what a Data Scientist is, let alone what courses they need to take.

You can’t have a discipline without someone selling you a journal catering to that discipline.  In 2002, the Data Science Journal was launched, and in 2003, the Journal of Data Science was launched.  In 2005, The National Science Board published “Long-lived Digital Data Collections: Enabling Research and Education in the 21st Century” defining data scientists as “the information and computer scientists, database and software and programmers, disciplinary experts, curators and expert annotators, librarians, archivists, and others, who are crucial to the successful management of a digital data collection” whose primary activity is to “conduct creative inquiry and analysis.”

Tell that to a Data Scientist working at Microsoft and they will laugh.

This is the first blog post in my series on Data Science.  Over the course of the series, I will discuss many things that are critical to Data Science from what is a Data Scientist to Team Data Science Process (TDSP) to Algorithms and statistics.  Lets explore this new frontier together.

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