big data may 2012
DESCRIPTION
Presentation to BIG conference from May 2012TRANSCRIPT
![Page 1: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/1.jpg)
Big Dataopportunities forMarket Research
![Page 2: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/2.jpg)
Q. How big
is Big Data ?
![Page 3: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/3.jpg)
Byte B 100 1Kilobyte KB 103 1,000Megabyte MB 106 1,000,000Gigabyte GB 109 1,000,000,000Terabyte TB 1012 1,000,000,000,000Petabyte PB 1015 1,000,000,000,000,000Exabyte EB 1018 1,000,000,000,000,000,000
Computer Science 101
![Page 4: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/4.jpg)
A. Bigger than Shakespeare?
t1B
x 1000 =
1 KB
x 1000 =
1 MB
x 5 =
5 MB
![Page 5: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/5.jpg)
A. Bigger than your pocket?
x 100 =
500 MB
x 2 =
1 GB
x 60 =
60 GB
5 MB
![Page 6: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/6.jpg)
A. Bigger than the known universe?
60GB
1 TB
x 140 =
140TB
x 20 =
![Page 7: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/7.jpg)
A. Bigger than a day at Google?
2.5PB
x 5-10 =
140TB
x 11 =
13PB/year
1.5PB
x 1.5 =
20PB/day
or
![Page 8: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/8.jpg)
A. Bigger than the sum of human knowledge?
x 250 =
All words ever uttered by the human race since the beginning of time
5EB
20PB/day
![Page 9: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/9.jpg)
A. Bigger than the Internet?
x 100 =
All words ever uttered by the human race since the beginning of time
5EB
500EB
All data to flow across the Internet this year
![Page 10: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/10.jpg)
Pause to think…
These were the biggest data sets I could find statistics for
and both would be good raw material for Market Research
if we could find a big enough table to put them in
![Page 11: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/11.jpg)
There is a simpler answer
Q. How big is Big Data?
A. Bigger than we can easily handle
(and usually unstructured)
![Page 12: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/12.jpg)
Why now?
More activities are digital, creating “data exhaust”
More sensor devices creating digital data: “chips with everything”
More connectivity: data can be networked
Storage is cheap and getting cheaper
![Page 13: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/13.jpg)
Big Data means different things
Scientists: new frontiers of knowledge
IT industry: projects > 1 PB
Investors: opportunity for growth
Commerce: efficiency, decision-making
Google: business as usual
![Page 14: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/14.jpg)
Market leaders in commercial Big Data
Data ownership
Data Analytics
Data Storage
![Page 15: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/15.jpg)
Commercial applications for Big Data
Micro-segmentation / mass customisation
Predictive propensity modelling
Digital marketingPricing optimisation
Operational performance improvement
Forecasting
Product improvement / development
![Page 16: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/16.jpg)
The Big Data hypothesis for Market Research
“The availability of large quantities of consumer data
will allow us to generate new and/or lower cost
consumer insights through analysis of that data”
![Page 17: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/17.jpg)
Big Data sets for Consumer Insight
Social media
Web traffic
Transactional
Geodemographic& geolocation
![Page 18: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/18.jpg)
And let’s not forget qual and ethnography
Social media
Blogs
![Page 19: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/19.jpg)
A change in research process and mindset
Controllable sample
Extendable conclusions
Data on real world outcomes
Statistics
Analytics
Actionable insights
Hypothesis-led / inductive
Fact-led /Deductive
![Page 20: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/20.jpg)
Transferable Research skills
Understanding client needs
Asking/framing the right questions
Knowing what to look for
Interpretation
Synthesising insights
![Page 21: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/21.jpg)
And researchers have a grasp of statistical techniques used in data analysis
Pattern recognition
Trend analysis
Classification
Cluster analysis
Regression analysis
![Page 22: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/22.jpg)
Big Data firms want a piece of our action
Google Consumer Surveys
Facebook research
Dunnhumby entered the Honomichl 100
Nectar are launching an online panel
Big Data tells us what, but
not why
![Page 23: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/23.jpg)
How can Researchers respond?
1) Find a friendly data scientist
2) Get involved: understand available data sets
3) Talk to clients: what data? what needs?
4) Get creative: how could the data meet client needs?
5) Experiment (with your friendly data scientist)
6) Complement data with traditional research
![Page 24: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/24.jpg)
Success for Market Research in Big Data =
ResearcherData
scientistTechnology
+ x
![Page 25: Big data may 2012](https://reader037.vdocuments.site/reader037/viewer/2022103110/547e6046b4af9f62208b46e1/html5/thumbnails/25.jpg)
No-one is doing this well yet:
there is an open goal for whoever gets it right