What’s the Big Deal about Big Data?

52nd Annual ACMSE Conference

Jennifer Lewis Priestley, Ph.D.Professor of Statistics and Data Science

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Big Data – What is it?

Center for Statistics and Analytical Services at Kennesaw State University

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Big Data – What is it?

Center for Statistics and Analytical Services at Kennesaw State University

VOLUME

VELOCITY

VARIETY

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Big Data – What is it?Big Data (noun) – Condition present when the volume, variety, and velocity of data exceeds an organization’s storage or computing capacity for accurate and timely decision making.

It is NOT just about size.

Big Data – What is it?…but size (volume) is certainly part of the issue…

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Number of emails sent every second?2.9 Million

Video Uploaded to Youtube every minute?20 Hours

Amount of Data processed every day by Google?24 Petabytes

Tweets per Day?50 million

Orders Processed by Amazon every Second?73

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Big Data – What is it?…and the costs of storage are dropping…

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The total amount of digital data will reach 2.7 zettabytes by the end of this year. Approximately 80 percent of this data will be unstructured…

Big Data – What is it?

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Unstructured Data = Data

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 20200

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Structured Versus Unstructured Data Generated by Year

STRUCTUREDUNSTRUCTURED

Zett

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Big Data – Does it really matter?

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Jennifer’s Grandmother

We can’t do things the way we always have…

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We can’t do things the way we always have…

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Big Data Company 1: Coca Cola

~ 1500 machines around the world

Can dispense about 95 drinks an hour

Can dispense about 125 different drinks

Submits real time data on:- Syrup consumed/drink configuration- Outlet- Time

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Big Data Company 2: The Home Depot

~ 2300 stores globally

About 40,000 products in each store

Product pricing has to be dynamic

Thousands of vendors

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Big Data Company 3: The Southern Company

~ 4.6 million customers

~27,000 power distribution lines

Real time data, every customer

Advanced Metering Infrastructure

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What do these companies have in common?

They have all recognized the value of data to their operations.

They have all invested heavily in new hardware and software to capture and store their new data.

They have new hiring needs: Computer Scientists, Statisticians, Mathematicians

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This shift has huge implications for universities.

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We can’t teach the way we have always taught.

The 1950s called…they want their curriculum back…

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So, what does a 21st Century Curriculum look like?

Math, Stat, Computer Science…

Real Big, Real World Datasets…

Better Integration with Practitioners…

More Interdisciplinary Degrees…

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