Showing posts with label Analytics. Show all posts
Showing posts with label Analytics. Show all posts
Tuesday, September 6, 2016
Monday, May 4, 2015
Advantages Using Sensors and Big Data to help the Internet of Education (IoEd)
1. A sensor—something that
senses, captures, and reports information[1]
can be used by the education industry to improve student monitoring on an ongoing basis.
2. It adds to immediate care of
students by constant although through remote connectivity.
3. Cell phones could be used to
effectively track student locations through using global positioning systems (GPS). Radio frequency
identification (RFID) sensors are already in use in educational context.
4. Schools
can mine big data for segmentation, growth trending, to track student progress, assessment patterns and deviations if any.
5. Understand
gauge student reactions through interpreting voluminous data.
6. Be conversant with the sources
of data available to the decision makers.
7. View industry level data for
averages' computation and benchmarking.
8. Gleaning relevant information.
9. Big Data brings
together statisticians, IT data
specialists and business analysts for adding to business value.
10. Schools obtain an insight to
decision making. Teachers can achieve insight based on analysis of real data.
11. Schools get a macro perspective; there is the development of a mind-set
and behaviour against silos.
12. There is an added emphasis on shared data.
13. The school management has to perforce assimilate basic understanding of
analytical techniques so that they can utilize the results of big data
analytics effectively.
14. Aggregated datasets help evolve norms for access, security and privacy.
15. There is more professionalization in the education industry with requisite analytic skills being at a premium.
16. Decisions are not intuitive but based on confirmed big data.
17. Big data require schools to align their operational strategy and even their
mission to big data. Information needs of the school is viewed in totality.
18. Big data can
improve consistency, ensure accuracy
19. Big data necessitates and
accelerates standardization of data, processes for data usage, consequential communications
and best practices across the industry.
20. Schools need to redesign
their existing architecture and move to component based architecture.
21. Develops School information strategy.
***
The
copyright vests with the author. He can be contacted at jaynayar@gmail.com
[1]
Hewlett Packard (2015) The disruptive power of big data Business white paper
| HP Haven big data platform
Thursday, April 16, 2015
Internet of Things and GE's "brilliant" machines.
Jack Welch: GE will be around another 100 years
For General Electric (GE), the
Industrial Internet is a 'disruptive business model'.
General Electric estimates that the amount the Industrial Internet could add to
global GDP over the next 20 years is $ 15 trillion and that there would be about 50 billion
interconnected devices by 2020. By capturing the space offered by the Internet
of Things,
GE is trying to meet the customer
requirements of swift and instant gratification. GE is using the technological
surf of the IoT to ride the short term and to transform it to a long term wave
to enhance the return on investment. It hopes to make conversations between different
IT systems and have a unified set of meaningful
metrics. GE focuses on knitting together machines on a
common data platform. This should optimize industrial performance, enhance
values to the global supply chain, and add to ROI.
GE is keen to use the data generated
and make it more effective from an industrial angle through data sharing. GE seeks
to make manufacturing collaborative, decentralized, and efficient. Devices and
people across the globe will collaborate on production in real-time. There will
be a smart and efficient supply chain that is reliable and cost economic. Predictive
analytics will fuse "big iron" with "big data". [1]
GE is building partnerships with its Predix platform. This IoT `operating system’ originally developed for
GE's own use, is being utilised to help customer projects. It is proposed to make
it available to a growing number of technology
partners.
GE is positioning itself and is managing
for results. IoT's "power of one percent". The company
believes that using sensors and software to make current industrial procedures
and equipment just 1% more efficient will result in billions of saving for its
customers.
Savings at 1 % enhanced efficiency
|
Industry
|
Amount Saved in $
billion over 15 years
|
|
Oil & Gas
|
90
|
|
Health care
|
63
|
|
Aviation
|
30
|
Source: GE
The company now has more than 10 million sensors in the equipment it sells. The software analytics side of its business is expected to generate more than $1 billion in revenue. (GE's total revenue in 2013 was $146 billion). As the Predix software will be available to seekers, GE's IoT revenue will increase on volume basis.[2]
References
1. http://www.ge.com/stories/industrial-internet
2. http://www.fastcompany.com/3031272/can-jeff-immelt-really-make-the-world-1-better#9
3. http://diginomica.com/2015/03/11/general-electric-pursues-outcome-internet-things/
4. http://www.fool.com/investing/general/2014/11/05/general-electric-vs-cisco-which-is-the-better-inte.aspx
5. http://www.zdnet.com/article/ge-forges-internet-of-things-alliances-with-verizon-cisco-intel/
6. http://www.accenture.com/sitecollectiondocuments/pdf/accenture-industrial-internet-changing-competitive-landscape-industries.pdf
7. http://bits.blogs.nytimes.com/2014/10/09/ge-opens-its-big-data-platform/?_r=0
8. http://www.technologyreview.com/news/527381/ges-1-billion-software-bet/
9. http://ahmedbanafa.blogspot.in/2015/04/the-industrial-internet-of-things-iiot.html
Note : This script is based on
readings of the author during his on line research on the Internet of Things. The author can be contacted at jaynayar@gmail.com
[1] A
GE locomotive is made up of about 200,000 parts, contain 6.7 miles of wiring and 250 sensors
that put out 9 million data points every hour. These will increase rendering predictive
models of both performance and non performance possible. A single blade in a gas turbine, if you put a
lot of sensors on it, can generate 500 gigabytes of data each day; every pair
of GEnx engines, installed on Boeing's 787 Dream liner can generate a terabyte of information every day.
These devices
wouldn't just let you know they were going to break down. They would actually
repair themselves.
[2] GE
currently monitors and analyzes 50 million data points from 10 million sensors
on $1 trillion of managed assets daily. GE said it will open up the Predix
platform to users and developers in 2015. The platform allows for customized
industry apps, asset tracking and management and firewalls to protect
infrastructure.
Saturday, March 14, 2015
Internet of Things will bring about the dis-intermediation of bankers.
Internet of Things: The dis-intermediation of
bankers.
In
banking, the intervention of technology
has reached a critical threshold. The Internet of Things (IoT) revolution will
accelerate the age of disruption ushered in by the digitalization of banking. IoT will reduce dependence on bankers
but add to the customer accessibility of banking.
The components that would capture the attention of IoT in banking
include (a) development of sensor
platforms, (b) development of communication and connectivity systems,(c) cloud
computing (d) big data (e) analytics,
and (f) cyber security.[1]
Moore’s
Law states that there is a doubling of computer processing capacity every 18
months or so The “internet of things” uses multiple sensors
(like the brain’s neurons) connected through the web (like the brain’s
synapses) to create, in effect, a machine-brain.[2]
It is estimated that by 2020 there would be 30 billion wireless devices
connected to the Internet of things.[3]
These
requires that IoT reduces if not nullifies subjectivity. All processes would be
driven by integrated networking of technology and less by people. As banking
moves towards total technology driven banking, and as people operate from a
host of hardware interfaces through rapidly evolving software, there will be fewer bankers and more of
machines.
These mathematics
driven processes will cover the following functional areas through predictive models (using advanced analytics like data modelling, data
mining, statistical analysis, text mining and visualization can be used by
banks to ensure compliance to regulatory requirements by identifying patterns
and predictive trends.
a) Capital adequacy management;
b) Risk
management - Evaluation of risk exposure for internal and external - Risk Mitigation.
c) Real time assessment of factors
like the external market conditions, balance sheet changes.
d) Balance Sheet Management
e) Project performance
management.
f) Fraud detection.
g) Credit risk
h) Customer profiling
i) Compliance
j) Payment / Settlement systems
k)
Trading of financial instruments (forex, bonds, other market instruments )
Without any risk or responsibility.
Copyright of this article and its contents vests with the author of this blog: Jayaram Nayar.
He can be contacted at email: jaynayar@gmail.com
[1] http://theinstitute.ieee.org/ieee-roundup/opinions/ieee-roundup/your-questions-answered-the-internet-of-things
[2] Haldane,
A. G. 'Growing Fast and Slow' Bank of England Speech at the East Anglia
University, 17 February, 2015
[3] Padmanabhan, G 'Emerging Issues In Cyber
Security in The Financial Sector' Reserve Bank
of India, at the State Bank of Travancore, , 28 February
2015.
Subscribe to:
Posts (Atom)