We have
been hearing a great deal about Big Data in the last few years. What is this
hype about? Why the hype? The hype says that with more data we can gather the
better answers to business problems. My first exposure to Big Data was at the
University of Arizona’s 2014 Symposium on
Data Analytics in Healthcare held on October 17, 2014. At the time, my team
of healthcare management consultants for the University of Arizona Medical Center,
decided to attend this symposium to understand the hype and how Big Data is
helping the healthcare sector. I am sure, that we have all read that the
healthcare industry is under pressure to reduce the cost of care, while improve
patient care. The various technologies such as Electronic Health Records (EHR),
social media, cellular applications, etc. are pressuring healthcare to dive
into the Big Data treasure hunt in order to find ways to improve patient care
and reduce overall costs. The speakers at the symposium discussed various
topics, projects, and research related to social media (such as twitter) and
cellular applications to monitor and improve the healthcare. Nonetheless to
say, the symposium was great exposure to various aspects and use of Big Data
that sparked an interest in me.
So the
question is what and how Big is Big Data? Big data is an evolving term that
describes a massive volume of data that is difficult to process with
traditional software and database techniques. We live in a world where
technology is rapidly evolving. In return, we are sitting on a big data bomb,
with an expected volume exceeding 35 Zettabytes by 2020. I am sure you are
wondering, well how much is Zettabytes (see picture below for a hierarchical
explanation of Zettabyte)? Ok, so think about a cup of coffee (1 Gigabyte) and
compare it to the Great Wall of China – have the picture? Well that is a visual
explanation of a Zettabyte.
As part of the Business
Intelligence lecture and readings for Week 1, I was mind-blown about the amount
of data being generated in 60 seconds:
·
More
than 100,000 tweets
·
More
than 400,000 Skype calls
·
More
than 80,000 posts on Facebook
·
200,000
e-mails sent
·
700,000
searches on Google
Can you
believe it? Are you as shocked as I was? Isn’t this miraculous!? In 2010, Eric
Schmidt from Google expressed “There were 5 exabytes of information created
between the dawn of civilization through 2003, but that much information is now
created every 2 days.”
So based
on my blog so far, you are tempted to understand big data merely in terms
of size but of course, you would be misled. In addition to volume, big data is
characterized by volume and its ability to transform into data many aspects of
the world that were previously unimaginable, such as GPS signals from cell
phones, likes on Facebook, messages and images posted on social networks,
readings from sensors, such as vending machines, car seats, jet engines, etc. Las
but not least, the speed of data creation is another important aspect of Big
Data. Real-time data makes it possible for businesses to understand their
position in the market at the exact moment and become more agile than their
competitors. In simplest terms, because of big data businesses can now measure,
and understand a lot more about how they operate, and translate all that
knowledge into improved decision-making and performance.
So, how
can we deal with the variety, volume and velocity of Big Data? The answer is
Business Intelligence BI). BI is the applications, technologies, tools and
techniques that are used to gather and analyze data in order to provide businesses
with actionable insights on measuring and managing their performance. Important
thing worth noting is that BI is based on data and data needs to be accurate in
order to get the benefit of it. There are numerous activities embedded within
BI, such as analytics, data warehousing, data collection and processing, data
mining, reporting and querying software, digital dashboards. As, Peter
Sondergaard from Gartner Research said, “Information is the oil of the 21st
century, and analytics is the combustion engine.”
Big data
and BI are used in many industries, from manufacturing, to healthcare, from law
enforcement to environment, from traffic control to fraud prevention, etc. The exponential
growth of data will require need for BI related jobs. Based on a recent report
from McKinsey, United States will require about 200,000 data scientists (an
individual that can combine analytical, technical, quantitative and business skills)
and 1.5 million data savvy managers.
In
closing, if we think Big Data is big now, we just have to wait …
References
Cukier, K. N., & Mayer-Schoenberger, V. (2013). The Rise of Big
Data. Foreign Affairs.
McAfee, A.,
& Brynjolfsson, E. (2012). Big Data: The management revolution. Harvard
Business Review.
Miller, R.
(2014, Aug 10). If You Think Big Data's Big Now, Just Wait. Retrieved
from Tech Crunch:
http://www.techcrunch.com/2014/10/big-data-bound-to-get-really-really-big-with-the-internet-of-things
Ram, S. (2015). Intro to Big
Data and Business Intelligence. Module 1
