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Cloud Computing and the Process Integration Era
The Industry Advisory Council (IAC) is a non-profit, non-partisan organization dedicated to fostering improved communications and understanding between government and industry. through its affiliation with the American Council for Technology…
The Tactical Cloud
When cloud computing first came in vogue, there was a rather serious discussion about the private cloud concept. The whole idea of cloud computing seemed to argue against implementing such…
“Cloud Musings” Now on SYS-CON Media “Cloud Computing Journal” !!
I’m happy to announce that a recent “Cloud Musings” article, “Commercial vs Federal Cloud Computing ” has been reposted on SYS-CON Media’s “Cloud Computing Journal“. Thank you SYS-CON for making…
How to make clouds interoperable and standard !!
This has been a huge part of my life over the past few weeks! This is my personal view. WARNING: DON’T EXPECT THE ANSWER TO BE FOUND BELOW !!! There…
The Tension between Public and Private Clouds
Last week, during discussion on cloud interoperability and standards in Israel, I saw for the first time a real dichotomy in the value of public (external) and private (internal) clouds.…
Cloud Computing for Continuity of Operations (COOP)
Recently, I’ve been focusing on cloud computing for COOP. The way I looked at it, many government agencies are already using commercial shared facilities as COOP sites and that the…
NCOIC Plenary Session
Hopping a plane to the west coast today to attend the NCOIC Plenary in Costa Mesa, California. First day “Cloud Computing for Net-Centric Operations” agenda includes: David Ryan, Chief Architect…
Dataline named “Top 100 Cloud Computing Company”
SYS-CON’s Cloud Computing Journal included Dataline in its expanded list of the most active players in the cloud ecosystem. In adding Dataline to the “Top 100” list, Jeremy Geelan noted…
Autoscaling into the cloud- Good or Bad?
I always thought saw the ability to autoscale into a cloud infrastructure as a good thing. George Reese presented a differing view on the O’Reilly blog recently. “Auto-scaling is the…
Cloudera must be reading the script!
“Cloud computing leapt out as the most obvious way to address enterprise large data problems” – Ken Pierce, IT Specialist, DIA-DS/C4ISR “We view Hadoop as the key enabler…[in] optimizing the…
- 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.
Cognitive systems understand by interaction, reason by generating recommendations and hypotheses, and learn from human experts and data. Since they never stop learning they also never stop providing business value. With this blending of cloud infrastructure and cognitive applications, the impossible can suddenly become easy!
- 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.
Industry
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Cloud Computing
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Cognitive Computing
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Cyber security
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Highly automated and economical infrastructure platforms that encompass the implementation and enforcement of “brutal standardization” – IaaS
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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
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Marketing
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Ubiquitous access to compute, storage and networking services independent of device
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Delivery of social media analytics that promise the coordinated delivery of context driven information and commercial offers across multiple channels to targeted individuals
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Process Industries
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Connectivity to over 6.4 billion sensors collecting and storing real-time data
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Analytics and cognitive computing programs that provide actionable insight from real-time and historic data
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All industry verticals
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Transform from the delivery of labor hours and physical goods to the delivery of information and services (Uber, Air B&B, Travelocity, etc)
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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 (https://www.tomsitpro.com/articles/ibm-cloud-hyrid-storage-watson,1-3158.html)
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Consulting / Analytics
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Voice-driven command and control
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Applications that understand natural language and generate personalized insights that learn with every user interaction
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Consulting
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Economic and secure collection, transport, processing and storage of massive amounts of structured and unstructured data
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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.”
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Distribution / Publishing / Content Management
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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.
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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.
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Education / Research
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Global SaaS/PaaS business models and platforms
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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.
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Healthcare / Public Safety
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Global SaaS/PaaS business models and platform
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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.
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Cloud Computing
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