Week One -- The Big (Data) Bang

I attended high school in the mid-1980s.  Back then, the “Internet” was the public library.   Almost everything I needed to know was contained in volumes of books stacked neatly on rows of shelves.  Googling something meant thumbing through a massive compilation of 3x5 Dewey Decimal cards.  Personal computers like the Apple II and Commodore 64 were in their infancy, and electronic data storage was microscopic compared to today’s standards.

In 1994, the year I graduated from college, our computer lab had recently upgraded their servers to one gigabyte hard drives.  I remember being amazed by the capacity of these drives.  A gigabyte seemed beyond my comprehension.  The hard drive on my personal computer could store only 50 megabytes.  I felt that one gigabyte was more than you could ever use.

Fast forward to the year 2015.  The Information Age is in full swing.  My personal computer has a hard drive capacity 2,500 times the size of that one gigabyte server.  We have reached a point where all collective digital data can be measured in zettabytes.  This strange sounding number represents the capacity of one trillion of those gigabyte hard drives.  According to a study by the IDC, digital content will reach 40 zettabytes by 2020¹.

The reason for this explosive growth can be observed in our daily activities.  Consider the following sampling of online actions that occur every minute²:

•  Facebook users share 2.5 million pieces of content.
• Twitter users tweet 277,000 times.
• Instagram users post nearly 220,000 new photos.
• YouTube users upload 72 hours of new video content.
• Apple users download 48,000 apps.
• Email users send over 200 million messages.
• Amazon generates over $80,000 in online sales.

This massive and rapidly growing digital universe is often referred to as “big data.”  While the word big seems like an understatement, it is comparable to an astronomer’s reference to the Big Bang.  Both events represent a massive expansion and transformation from very humble beginnings.  Both continue to expand at a mind-boggling rate.  And both are in integral part of the world and universe we now live in.

For example, when I go shopping at my local grocery store, I hand my loyalty card to the cashier.  Every item I purchase is recorded and added to a database.  I always pay with a credit card to get points, and this transaction is added to my purchase history in the credit company’s a data repository.  The cell phone in my pocket provides my general location to my provider.  My Apple Health app records the distance I walk at the store.  And the list goes on and on. 

This stream of captured personal data represents the “datafication” of our world.  Collectively, we are being classified by the data footprint we create.  Whether it is through purchases, status updates, emails, tweets or cell phone calls, we are contributing to our big data profile.  Companies are increasingly using this data to make business decisions and map out their strategy.

               "Datafication is the idea that more and more businesses are dependent
               on their data for their business.³"

Information Week makes the analogy that datafication has the same impact as electrification did in the late 1800s³.  Just as we cannot imagine a company operating without electricity, today’s businesses are reliant on their information systems’ infrastructure and the collection of big data.  The appetite for such data is insatiable because it offers the possibility of a competitive advantage and profit.  Advertising and marketing can be more effectively targeted.  Applications can become more convenient and useful as they are tailored to our individual habits and preferences.  In one estimate, $72 billion in financial value was derived by European companies that utilized customer data³. 

To realize such positive returns on big data, it needs to be effectively understood and utilized.  In its raw form, big data is a huge, ever-growing, convoluted maze with compartments of segregated information.  It can be structured such as transactions stored on an internal server.  Or it can be unstructured in the form of text on social media. 

This is where Business Intelligence (BI) plays a very important role; it uses big data to produce meaningful insights that can be acted upon by an organization or individual.  Simply having large quantities of data is not useful.  As Harvard Magazine points out, “There is a big data revolution.... But it is not the quantity of data that is revolutionary.  The big data revolution is that now we can do something with the data⁵.”  Data scientists are linking big data in its various forms and creating visualizations thus making it more meaningful and building predictive models.

As data continues to become bigger, the demand for BI will grow with it.  Data professionals such as business analysts, data warehouse analysts, and data scientists are increasingly in demand.  The University of Arizona recognized the important role big data and BI play in today’s Information Age.  Consequently, they added a Business Intelligence track to its MIS Master’s program.  This class is the capstone of the series.

Even though I still wax a little nostalgic for my library card and Apple IIe computer, Business Intelligence is an interesting and exciting topic of study.  It’s a brave new data world.

1.       Gantz, John and Reinsel, David.  2012 December.  “THE DIGITAL UNIVERSE IN 2020: Big Data, Bigger Digital Shadows, and Biggest Growth in the Far East.”   IDC IVIEW.  https://www.emc.com/collateral/analyst-reports/idc-the-digital-universe-in-2020.pdf.

 

2.       Gunelius, Susan.  2014 July 12.  “The Data Explosion in 2014 Minute by Minute – Infographic.”  ACI.   http://aci.info/2014/07/12/the-data-explosion-in-2014-minute-by-minute-infographic/.

 

3.       Bertolucci, Jeff.  2013 February 25.  “Big Data's New Buzzword: Datafication.”  InformationWeek.  http://www.informationweek.com/big-data/big-data-analytics/big-datas-new-buzzword-datafication/d/d-id/1108797.

4.       Regalado, Antonio and Leber, Jessica.  2013 May 20.  “Intel Fuels a Rebellion Around Your Data.”  MIT Technology Review.  http://www.technologyreview.com/news/514386/intel-fuels-a-rebellion-around-your-data/.

5.       Shaw, Jonathan.  2014 March - April.  “Why ‘Big Data’ Is a Big Deal.”  Harvard Magazine.  http://harvardmagazine.com/2014/03/why-big-data-is-a-big-deal.

A Brief Introduction: My Mid-Life Crises Theory

When young, people ask what you want to be when you grow up.  The possibilities have no limits when your age is in the single digits.  Becoming an astronaut seems no more difficult than working as a burger flipper at McDonalds.

As time and circumstance happen to everyone, the possibilities narrow.  Decisions are made that set a person on a path that becomes harder and harder to change.  Choosing a college, a major, a career and a spouse begin to cast the mold of a person’s life.

Now consider my mid-life crises theory:  Once we reach the approximate mid-point of our life, our brains begin to weigh the aspirations we had when young to how things are actually turning out.  Many of us discover that we didn’t become the astronaut who travels to the moon.  Instead, we drive an economical car to a generic office building and sit in a small cubicle typing on our computers.

Sometimes this can lead to changing our course is some shape or form.   Maybe it is buying the uneconomical sports car.  Or maybe it is changing jobs or going back to school.  Whatever the change, it affords the feeling of having some semblance of control still -- that maybe there are still endless possibilities.

As I approached middle age, I made several such course corrections.  For the most part, I was happy with my life.  However, unexpected life events can result in unforeseen changes.  This is what happened to me.  After working over 17 years for one of the largest financial institutions in the country, I saw the writing on the wall.  The company was outsourcing its information systems at a quickening pace.  People I had worked with for years were let go.  Soon, I was the only original member left on my team.

To prepare for the inevitable, I retired from the National Guard.  I knew from watching other Soldiers how hard it can be looking for a job when a potential employer knows that you can be called away from work.  I also knew it was time to refresh the schooling on my resume.  Consequently, I enrolled in the Master’s in MIS online program at the University of Arizona (UA).

As anticipated, I was told that I could either transfer to Ohio to continue my employment or take a severance.  My decision was to part ways and chart a new course.   With the money from my severance, and with the help of the G.I. Bill, I focused on my degree.  After graduation, I will see what new opportunities I can find.

The “Business Intelligence” named in the blog title represents one of my last two classes.  If all goes as planned, I will be graduating this December.  This blog will contain my thoughts and observations on topics covered in class over the next seven weeks.