Cloud computing has
taken over the business world! With almost maniacal focus, single
proprietors and Board Directors of the world’s largest conglomerates see this
new model as a “must do”. This rapid shift is, in fact, accelerating. As Jeff
Bertolucci observes in “The
Shift to Cloud Services Is Happening Faster Than Expected”:
“According to the sixth annual Uptime Institute Data Center Industry Survey, which
examines the big-picture trends shaping IT infrastructure delivery and
strategy, the move to cloud services is accelerating. The Uptime Institute’s
February 2016 poll of more than 1,000 data center and IT professionals predicts
that an even faster shift to the cloud will occur over the next four years,
reports ZDNet.”
Another maybe even
more important trend, that is actually being driven by cloud computing, is the
rapid expansion of cognitive
computing. In this arena, IBM’s Watson, famously known for defeating
Jeopardy gameshow champions Ken Jennings and Brad Rutter,
has quickly established itself as a commercial cognitive computing powerhouse. Contemporary
reports of the Jeopardy contest from the New York Times cited this victory as
IBM’s “…proof that the company has taken a big step toward a world in which
intelligent machines will understand and respond to humans, and perhaps
inevitably, replace some of them”. Although we are not yet at the human
replacement stage, the merger of cloud and cognitive computing is rocking the
business status quo.
Coined as “Cognitive Business” this trend can deliver
quantum level improvement to just about any industry vertical. Examples
include:
- Using highly automated and economic cloud infrastructure to deliver proactive and predictive monitoring and threat interception in cybersecurity;
- Leveraging cloud computing device independence to enable real-time social media analytics that coordinate delivery of context driven information and commercial offers across multiple marketing channels;
- Establishing connectivity across over 6.4 billion sensors so that analytics and cognitive computing programs can provide actionable insight from real-time and historic data; and
- Hybrid Cloud data architectures that use cognitive computing capabilities to maintain content traceability and lifecycle management to enable the auditable management of licenses, terms of use, and changes to third-party data.
If your business wants to take advantage of this important
transition, the time to take action is now. Your initial steps should include:
- Develop a cognitive strategy by deciding which of your products, services, processes and operations should be infused with cognition. Your strategy should include identifying your organizations data needs and picking the experts to train the cognitive system.
- Collect and curate the data that is most useful to driving your business model. This step will help in creating an organizational foundation of data and analytics.
- Use cloud services that are designed specifically for your industry vertical. Such services will incorporate the application programming interface (API) building blocks necessary to power your future cognitive products and services.
- Acquire hybrid cloud service broker expertise and develop a hybrid infrastructure transition plan that combines your current IT systems with private and/or public clouds. This combination will serve as a backbone of your cognitive business.
- Establish and build-in a data-centric security model from the start. This focus will give you the ability to secure every transaction, piece of data and interaction as cognitive systems make their way into the Internet-of-Things (IoT). Secure systems ensure trust in the entire system and ultimately, the organization’s reputation.
(Five Ways To Build A Cognitive Business, http://www.forbes.com/sites/ibm/2015/11/16/five-ways-to-build-a-cognitive-business/#2b1a28174e9e)
Industry
|
Cloud Computing
|
Cognitive Computing
|
Cyber
security
|
Highly
automated and economical infrastructure platforms that encompass the
implementation and enforcement of “brutal standardization” - IaaS
|
Enables the
advancement of operational cyber security is from threat detection via
signature-based identification to proactive and predictive monitoring and
threat interception powered by analyzing user behavior
|
Marketing
|
Ubiquitous
access to compute, storage and networking services independent of device
|
Delivery of social
media analytics that promise the coordinated delivery of context driven
information and commercial offers across multiple channels to targeted
individuals
|
Process
Industries
|
Connectivity
to over 6.4 billion sensors collecting and storing real-time data
|
Analytics and
cognitive computing programs that provide actionable insight from real-time
and historic data
|
All industry verticals
|
Transform
from the delivery of labor hours and physical goods to the delivery of
information and services (Uber, Air B&B, Travelocity, etc)
|
In the case
of IBM Watson, the consumption and processing of billions of API calls per
month across 80,000 programs developed by 500 companies in 36 countries
(http://www.tomsitpro.com/articles/ibm-cloud-hyrid-storage-watson,1-3158.html)
|
Consulting /
Analytics
|
Voice-driven
command and control
|
Applications
that understand natural language and generate personalized insights that
learn with every user interaction
|
Consulting
|
Economic and
secure collection, transport, processing and storage of massive amounts of
structured and unstructured data
|
Ability to pull non-obvious insights out of
massive amounts of multi-structured data through the discovery of patterns
and relationships. This enables the economic use of dark data, described as
"information assets that organizations collect, process and store in the
course of their regular business activity, but generally fail to use for
other purposes."
|
Distribution
/ Publishing / Content Management
|
Hybrid Cloud
data architectures that ensures that, when multiple data zones are in use,
compute power is moved to the data, rather than compute workloads being moved
in a way that could violate institutional policies, regulatory guidelines or
governmental laws around data location.
|
Data Fabric
technology that maintains the traceability and lifecycle of content enabling
the auditable management of licenses, terms of use, and changes to
third-party data.
|
Education /
Research
|
Global
SaaS/PaaS business models and platforms
|
Creation of
Analytic Fabrics that combine and orchestrate different analytics engines
that deliver an ability to create composite or cognitive insights across
first-part and third-party data. This can also be used to combine natural
language queries with structured data analytics.
|
Healthcare /
Public Safety
|
Global
SaaS/PaaS business models and platform
|
Cognitive Graphs that can represent entities, relationships, and
attributes in a probabilistic way, not just a deterministic way, so that
users can do inferencing and generate hypothesis. This also delivers an
ability to normalize many different data types as well as learn from data
over time. With this capability, when something changes somewhere in the
graph that may affect something elsewhere in the graph, every specific change
is recognized at every point it touches.
|
Figure 2-
Cloud and Cognitive Computing Merge to drive business value in multiple
industry verticals
( This post was brought to you by IBM Global Technology Services. For more content like this, visit Point B and Beyond.)
( Thank you. If you enjoyed this article, get free updates by email or RSS - © Copyright Kevin L. Jackson 2015)
2 comments:
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