SlideShare a Scribd company logo
How Big is Data?
And How Big is Data Going to Be?
Chris Gladwin
Top 10 Strategic Technology Trends for 2016
Source: Gartner
Top 10 Strategic Technology Trends for 2016
Source: Gartner
Gladwin’s Law:
Better Technology =
More Data
(a LOT more data)
Human Genomes
Medical
Consumer
Research
$10M
In 2006
$3B
In 2003
$1K
In 2014*
3
HD
1K
TV
.5K
UHD
4K
UHD-2
8K
Digital Video
Digital
Video
Phone
Video
Demand is Growth on Growth
* Illumina HiSeq X Ten
Plus Camera Phones, Lidar, Satellites, Microscopes, Seismographs, MRIs, X-Rays,
Telescopes, Radio Telescopes, Spectrum Observatories, Cars, Aircraft Engines, etc.
Network Management
Enterprise
Network
Metadata
2025
3.3 PB
2020
1.0 PB
2015
0.4 PB
Data growth challenge
Enterprise Exabytes Deployed per Year (millions of Terabytes)
0
20
40
60
80
100
120
2009 2010 2011 2012 2013 2014 2015 2016 2017
Unstructured content
Structured data
Source: IDC
Capacity
increase
60–80%
per year
Unstructured
will be
79%
of all new
data
Cloud = Larger Storage Systems
5
Enterprise
Medium Business
Small Business
PCs
Future
Medium
Business
Small Business
PCs
Public Clouds
Enterprise
Private Clouds
Past
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2004 2014 2024
Worldwide Enterprise Storage Deployments
Storage
Capacity
Deployed
Per System
Zettabyte
x 1000
Exabyte
x 1000
Petabyte
x 1000
Terabyte
Source: IDC
Data analysis challenge
Enterprise Exabytes Deployed per Year (millions of Terabytes)
0
20
40
60
80
100
120
2009 2010 2011 2012 2013 2014 2015 2016 2017
Unstructured content
Structured data
Source: IDC
20 Exabytes of
Structured Data
in 2017
Implications
20 Exabytes of Structured Data in 2017
90% is archived and never read
10% of records are read
Up to a minute response on data reads
Average record is 500 bytes
77,000,000,000,000 reads per second!
Data AND Data Analysis Growth
Computers, sensors, and machines
are creating evermore digital data
Trillions of
Records
Billions of
Queries
per Second
Organizations
Need to Analyze
All This Data
Computers, with machine learning, are
required to analyze data at this scale
Thank You

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BDW Chicago 2016 - Chris Gladwin, Founder Cleversafe & Ocient - How Big Is Data? And How Big is Data Going to Be?

  • 1. How Big is Data? And How Big is Data Going to Be? Chris Gladwin
  • 2. Top 10 Strategic Technology Trends for 2016 Source: Gartner
  • 3. Top 10 Strategic Technology Trends for 2016 Source: Gartner Gladwin’s Law: Better Technology = More Data (a LOT more data)
  • 4. Human Genomes Medical Consumer Research $10M In 2006 $3B In 2003 $1K In 2014* 3 HD 1K TV .5K UHD 4K UHD-2 8K Digital Video Digital Video Phone Video Demand is Growth on Growth * Illumina HiSeq X Ten Plus Camera Phones, Lidar, Satellites, Microscopes, Seismographs, MRIs, X-Rays, Telescopes, Radio Telescopes, Spectrum Observatories, Cars, Aircraft Engines, etc. Network Management Enterprise Network Metadata 2025 3.3 PB 2020 1.0 PB 2015 0.4 PB
  • 5. Data growth challenge Enterprise Exabytes Deployed per Year (millions of Terabytes) 0 20 40 60 80 100 120 2009 2010 2011 2012 2013 2014 2015 2016 2017 Unstructured content Structured data Source: IDC Capacity increase 60–80% per year Unstructured will be 79% of all new data
  • 6. Cloud = Larger Storage Systems 5 Enterprise Medium Business Small Business PCs Future Medium Business Small Business PCs Public Clouds Enterprise Private Clouds Past
  • 7. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2004 2014 2024 Worldwide Enterprise Storage Deployments Storage Capacity Deployed Per System Zettabyte x 1000 Exabyte x 1000 Petabyte x 1000 Terabyte Source: IDC
  • 8. Data analysis challenge Enterprise Exabytes Deployed per Year (millions of Terabytes) 0 20 40 60 80 100 120 2009 2010 2011 2012 2013 2014 2015 2016 2017 Unstructured content Structured data Source: IDC 20 Exabytes of Structured Data in 2017
  • 9. Implications 20 Exabytes of Structured Data in 2017 90% is archived and never read 10% of records are read Up to a minute response on data reads Average record is 500 bytes 77,000,000,000,000 reads per second!
  • 10. Data AND Data Analysis Growth Computers, sensors, and machines are creating evermore digital data Trillions of Records Billions of Queries per Second Organizations Need to Analyze All This Data Computers, with machine learning, are required to analyze data at this scale

Editor's Notes

  1. From Gartner Symposium
  2. From Gartner Symposium