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DISA Chief Technologist States Plan for Cloud
In an interview reported on in this month’s Military Information Technology magazine, David Mihelcic, DISA Chief Technology Officer, has laid out his goal for the agency’s cloud computing initiative. As…
Google, GeoEye, Twitter. What a Combination!
On September 9th, Bob Lozano posted his kudos to GeoEye for a successful launch of GeoEye-1. (Hey Bob! Where’s that post on your “cloud failure” last week?) According to their…
RightScale goes Transcloud
Over the weekend, Maureen O’Gara of SYS-CON media reported that RightScale is now offering a “first in industry” capability to provide application management across multiple cloud infrastructures. It now offers…
A Bill to Outlaw Cloud Computing…..
… is what we may see if we don’t educate our lawmakers now! That seemed to be one of the main point at last week’s Google workshop in DC. Berin…
Military Information Technology Cloud Computing Collaboration
Today, we’re happy to announce what we believe to be an industry first. “Military Information Technology Magazine“, as the publication of record for the defense information technology community, is collaborating…
Is 99.999% reliability good enough?
According to Reuven Cohen in his recent post, Cloud Failure: The Myth of Nines , the whole concept of reliability may be meaningless. “In the case of a physical failure…
You Probably Use Cloud Computing Already.
56% of internet users use webmail services such as Hotmail, Gmail, or Yahoo! Mail. 34% store personal photos online. 29% use online applications such as Google Documents or Adobe Photoshop…
20 Real-Life Challenges of Cloud Computing
Nikita Ivanov of GridGain offers some excellent insight into the nuts and bolts of getting the cloud to work. Definitely worth a read. To summarize: Most likely you do NOT…
3Tera Announces Global Cloud Services
Last week, 3Tera has announced the availability of global cloud services, based on their AppLogic grid operating system. 3Tera is currently running data centers in seven countries (United States, Japan,…
- 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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( 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)
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