SlideShare verwendet Cookies, um die Funktionalität und Leistungsfähigkeit der Webseite zu verbessern und Ihnen relevante Werbung bereitzustellen. Wenn Sie diese Webseite weiter besuchen, erklären Sie sich mit der Verwendung von Cookies auf dieser Seite einverstanden. Lesen Sie bitte unsere Nutzervereinbarung und die Datenschutzrichtlinie.
SlideShare verwendet Cookies, um die Funktionalität und Leistungsfähigkeit der Webseite zu verbessern und Ihnen relevante Werbung bereitzustellen. Wenn Sie diese Webseite weiter besuchen, erklären Sie sich mit der Verwendung von Cookies auf dieser Seite einverstanden. Lesen Sie bitte unsere unsere Datenschutzrichtlinie und die Nutzervereinbarung.
Data is the new oil. Our ability to make use of ALL data anytime anywhere is transforming our world.
Data plays a key role in every single one of these trends.
AI and Advanced Machine LearningArtificial intelligence (AI) and advanced machine learning (ML) are composed of many technologies and techniques (e.g., deep learning, neural networks, natural-language processing [NLP]). The more advanced techniques move beyond traditional rule-based algorithms to create systems that understand, learn, predict, adapt and potentially operate autonomously. This is what makes smart machines appear "intelligent." "Applied AI and advanced machine learning give rise to a spectrum of intelligent implementations, including physical devices (robots, autonomous vehicles, consumer electronics) as well as apps and services (virtual personal assistants [VPAs], smart advisors), said Mr. Cearley. "These implementations will be delivered as a new class of obviously intelligent apps and things as well as provide embedded intelligence for a wide range of mesh devices and existing software and service solutions." Intelligent AppsIntelligent apps such as VPAs perform some of the functions of a human assistant making everyday tasks easier (by prioritizing emails, for example), and its users more effective (by highlighting the most important content and interactions). Other intelligent apps such as virtual customer assistants (VCAs) are more specialized for tasks in areas such as sales and customer service. As such, these intelligent apps have the potential to transform the nature of work and structure of the workplace. "Over the next 10 years, virtually every app, application and service will incorporate some level of AI," said Mr Cearley. "This will form a long-term trend that will continually evolve and expand the application of AI and machine learning for apps and services." Intelligent Things Intelligent things refer to physical things that go beyond the execution of rigid programing models to exploit applied AI and machine learning to deliver advanced behaviors and interact more naturally with their surroundings and with people. As intelligent things, such as drones, autonomous vehicles and smart appliances, permeate the environment, Gartner anticipates a shift from stand-alone intelligent things to a collaborative intelligent things model. Virtual and Augmented RealityImmersive technologies, such as virtual reality (VR) and augmented reality (AR), transform the way individuals interact with one another and with software systems. "The landscape of immersive consumer and business content and applications will evolve dramatically through 2021," said Mr. Cearley. "VR and AR capabilities will merge with the digital mesh to form a more seamless system of devices capable of orchestrating a flow of information that comes to the user as hyperpersonalized and relevant apps and services. Integration across multiple mobile, wearable, Internet of Things (IoT) and sensor-rich environments will extend immersive applications beyond isolated and single-person experiences. Rooms and spaces will become active with things, and their connection through the mesh will appear and work in conjunction with immersive virtual worlds." Digital Twin A digital twin is a dynamic software model of a physical thing or system that relies on sensor data to understand its state, respond to changes, improve operations and add value. Digital twins include a combination of metadata (for example, classification, composition and structure), condition or state (for example, location and temperature), event data (for example, time series), and analytics (for example, algorithms and rules). Within three to five years, hundreds of millions of things will be represented by digital twins. Organizations will use digital twins to proactively repair and plan for equipment service, to plan manufacturing processes, to operate factories, to predict equipment failure or increase operational efficiency, and to perform enhanced product development. As such, digital twins will eventually become proxies for the combination of skilled individuals and traditional monitoring devices and controls (for example, pressure gauges, pressure valves). Blockchain and Distributed LedgersBlockchain is a type of distributed ledger in which value exchange transactions (in bitcoin or other tokens) are sequentially grouped into blocks. Each block is chained to the previous block and recorded across a peer-to-peer network, using cryptographic trust and assurance mechanisms. Blockchain and distributed-ledger concepts are gaining traction because they hold the promise to transform industry operating models. While the current hype is around the financial services industry, there are many possible applications including music distribution, identity verification, title registry and supply chain. "Distributed ledgers are potentially transformative but most initiatives are still in the early alpha or beta testing stage," said Mr. Cearley. Conversational SystemThe current focus for conversational interfaces is focused on chatbots and microphone-enabled devices (e.g., speakers smartphones, tablets, PCs, automobiles). However, the digital mesh encompasses an expanding set of endpoints people use to access applicatons and information, or interact with people, social communities, governments, and businesses. The device mesh moves beyond the traditional desktop computer and multiple devices to encompass the full range of endpoints with which humans might interact. As the device mesh evolves, connection models will expand and greater cooperative interaction between devices will emerge, creating the foundation for a new continuous and ambient digital experience. Mesh App and Service ArchitectureIn the mesh app and service architecture (MASA), mobile apps, web apps, desktop apps and IoT apps link to a broad mesh of back-end services to create what users view as an "application." The architecture encapsulates services and exposes APIs at multiple levels and across organizational boundaries balancing the demand for agility and scalability of services with composition and reuse of services. The MASA enables users to have an optimized solution for targeted endpoints in the digital mesh (e.g., desktop, smartphone, automobile) as well as a continuous experience as they shift across these different channels. Digital Technology PlatformsDigital technology platforms provide the basic building blocks for a digital business and are a critical enabler to become a digital business. Gartner has identified the five major focal points to enable the new capabilities and business models of digital business — information systems, customer experience, analytics and intelligence, the IoT, and business ecosystems. Every organization will have some mix of these five digital technology platforms. The platforms provide the basic building blocks for a digital business and are a critical enabler to become a digital business. Adaptive Security Architecture The intelligent digital mesh and related digital technology platforms and application architectures create an ever-more-complex world for security. "Established security technologies should be used as a baseline to secure Internet of Things platforms," said Mr. Cearley. "Monitoring user and entity behavior is a critical addition that is particularly needed in IoT scenarios. However, the IoT edge is a new frontier for many IT security professionals creating new vulnerability areas and often requiring new remediation tools and processes that must be factored into IoT platform efforts."
This next section provides clear examples of innovating with data.
The Apple iWatch has a heart rate sensor
Everything can be measured. Cities are actively measuring air quality, water quality, traffic, transit, noise, weather, tides, people, anything that be sensed & measured.
Data is the new oil. Our ability to make use of ALL data anytime anywhere is transforming our world.
Every professional needs to become a citizen analyst in the data driven economy
With the data engineer data scientists will accomplish little.
A business leader needs a comprehensive view of data, analytics, and putting it to work
The chief data officer is growing fast… not sure what drove the plunge in Indeed’s data but instead focus on the trend line.
Graphic published with permission of ThotWave. https://www.thotwave.com/
Other possible adjectives: Controlled? Pedigreed? Grey Data? Black Data? Version control? The Data Self by Rob Horning http://thenewinquiry.com/blogs/marginal-utility/dumb-bullshit/
http://www.gartner.com/newsroom/id/2506315 “The underlying message of all these examples is that information is an asset in its own right. It has value. Gartner calls this emerging discipline of valuating information "Infonomics.It is not something of the far future, in fact, this is happening today in various industries, in commerce and public sector, in large and small enterprises.” However, Mr. Buytendijk underlined the fact that as exciting as all new business opportunities are, there are also reasons for concern. Concerning the ethics of big data, a recent Gartner Circle study showed that "governance and privacy" was the most important concern around big data – clearly there is a fine line between superior customer insight and being "creepy."
In partnership with Oceans of Data we brought a group of experts together from industry & academia to define data & analytics literacy. These are the top level recommendations.
Michael Bowen Associate Professor, Science Education, Mount Saint Vincent University, Halifax, Nova Scotia
Ben Davison Quantitative User Experience Researcher, Google
Rob Gould Faculty, UCLA Department of Statistics
Ryan Kapaun Crime Analyst, Eden Prairie Police Department
Cliff Konold Director, Scientific Reasoning Research Institute, University of Massachusetts, Amherst
Juan Miguel Lavista Ferres Principal Data Scientist at Bing/Microsoft
Odette Merchant Project Manager, Nova Scotia Community College (NSCC), Halifax, Nova Scotia, Canada
Andrew Schaffner Professor of Statistics, California Polytechnic State University, San Luis Obispo
Hunter Whitney Consultant, Author, and Instructor; UX and Data Visualization
Sponsored by Steven Miller IBM
Moderated by the Oceans of Data Team
Making better decisions requires confidence. Let’s talk about how Watson uses Cognitive to do just that.
In 2011 Watson competed against Ken Jennings & Brad Rutter. As we have all heard, Watson beat the best players in the world. Watson knew more, could answer faster, and pressed the button only when Watson determined its answer a high degree of confidence, otherwise it didn’t push the button at all. IBM donated the $1M prize to charity.
When doctors face challenges they face every day.. Their knowledge and experience is easily up to the task. Many problems they see, however are rare, or at least rare for them. What would happen if we applied Watson to one of the greater challenges of our time? Cancer
NCCN = National Comprehensive Cancer Network
This slide is self explanatory. Yes, Watson has proven to be quite adept at helping doctors diagnose and recommend treatment for cancers. Poor diagnoses are a huge burden on the cost of health care and an even bigger burden on the patient. If the correct treatmet is the 3rd or 4th one tried it’s often too late.