SEEQ CORPORATION
Big Data
Oregon Connections
Telecommunications Conference
Dustin Johnson
October 23, 2014
Introduction
•
Dustin Johnson
- Software architect and founding partner at Seeq
- Background in computer networks and distributed systems
•
- Founded on the premise that companies need better solutions for
quickly and easily deriving business insight from their Industrial Process
Data
- Leverages many classical Big Data tools and design patterns
2
What is Big Data?
•
•
Marketing term
English words
3
What is Big Data? - Problem
•
More data all the time
- The number of sensors is increasing at 30% every year
(The Economist – Building with big data, May 26th 2011)
- Corporate data is growing by 60% every year
(Gartner – Economic Intelligence Unit – Leveling the playing field 2011)
How valuable is data to competitive
advantage?
Data Usage
69%
0%-24%
27%
Extremely
valuable
Somewhat
valuable
Don't
know
> 75%
25%-49%
3%
0%
Not very
valuable
Not valuable at
all
Economist Intelligence Unit Survey, October 2010
50%-75%
Economist Intelligence Unit Survey, October 2010
4
What is Big Data? - Scalability
•
•
•
•
Scalability – Ability to make the system capability larger or smaller as needed. A
typical example is adding or removing computers from the system.
Emphasizes the scalability of a software system, often by leveraging distributed
computing
Scale is not just the volume of data, but can be computational resources, bandwidth,
memory, and reliability as well
Turns a technical problem into a business solution: More money = more capability
5
What is Big Data? - Opportunity
•
More data could equal more insight
- Opportunity to better know your
customers
- Opportunity to substantiate or
originate business ideas
•
Predicted $16.1 billion market for big
data in 2014 (Forbes 12/12/2013)
- Opportunity for tool and service
providers in the Big Data space
6
Where did Big Data come from?
•
•
The rise of the Internet-scale company in the
2000s
These business needs were challenging since
the data was
- Huge!
- And Growing!
•
These demands lead to
- Distributed Computation / Massively Parallel
Processing (MapReduce)
- NoSQL Databases (BigTable, Dynamo)
•
Many Big Data companies shared slightly out of
date concepts and even Open Source Software
(OSS)
7
What are the key technologies now?
•
Data Processing Platforms
•
Not Only SQL (NoSQL) Databases
8
Where is Big Data going?
•
Deeper into consumers (finer grained market
segmentation needs)
- Predictive analytics (Machine learning / Deep
Learning, Collaborative Filtering, ...)
•
Across industries (horizontal adoption)
- Many industries are just now beginning to look at Big
Data technologies
- Seeq is involved in bringing Big Data to the
Industrial/Process sector
9
Controversial Topics
•
Personal information
- Personal tracking (can be creepy)
- de-anonymizing (through introspection of data)
•
•
Security - New technology is
often paired with new security
challenges
Government
- Tug of war between individual
usefulness and government
usefulness
- Can resonate as “Big Brother”
- Precautions can be abused
10
But wait…what about the cloud?
•
•
•
Many Big Data technologies fit well with the cloud (remote datacenter)
paradigm
Most technologies aren’t exclusive to
the cloud
Many new markets (industrial
process being one of them) are
looking at alternatives
- Private clouds
- On premises datacenters
- IT managed solutions
11
SEEQ CORPORATION
End
References
•
The Economist – Building with big data, May 26th 2011
http://www.economist.com/node/18741392
•
Gartner – Economic Intelligence Unit – Leveling the playing field 2011
http://blogs.sap.com/wp-content/blogs.dir/15/files/2012/02/EIU_Levelling_The_Playing_Field_1.pdf
•
Economist Intelligence Unit Survey, October 2010
http://blogs.sap.com/wp-content/blogs.dir/15/files/2012/02/EIU_Levelling_The_Playing_Field_1.pdf
•
Forbes 12/12/2013
http://www.forbes.com/sites/gilpress/2013/12/12/16-1-billion-big-data-market-2014-predictions-from-idcand-iia/
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