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2017 Key Strategic technology trends


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2017 Gartner technology trends depicts some interesting technology facets and dimensions ; in essence , it will impact and compel technology providers and adopters to transform their business and strategic models in close alignment to these fluid yet revenue generating trend...I have attempted to articulate my interpretation of the technology trends .

Published in: Technology

2017 Key Strategic technology trends

  1. 1. 2017 KEY STRATEGIC TECHNOLOGY TRENDS SAMEER DHANRAJANI Global Business Leader, Cognizant Analytics & Data Sciences
  2. 2. 1. ARTIFICIAL INTELLIGENCE AND ADVANCED MACHINE LEARNING Applied AI and machine learning are composed of many technologies and techniques (such as deep learning, neural networks and natural-language processing [NLP]). The more-advanced techniques move beyond traditional rule- based algorithms to create systems that appear to understand, learn, predict, adapt and potentially operate with little or no human input or guidance. • Through machine learning, a smart machine can change its future behavior • Additionally, natural-language generation dynamically increases the volume and value of insights and context in data analytics. • Organizations are applying AI and machine-learning techniques to create intelligent app categories (such as VPAs) and improve traditional applications (such as worker performance analysis, sales and marketing, and security). REFERENCE LINKS and-ai-will-drive-digital-transformation/ revolution/
  3. 3. 2. INTELLIGENT THINGS Intelligent things are physical things that go beyond the execution of rigid programming models, leveraging AI and machine learning. This enables them to deliver advanced behaviors and interact more naturally with their surroundings and with people. Also, we can enhance existing things by embedding AI and machine learning invisibly into their normal operation. For example, we can turn a camera into a smart camera. • New intelligent things, built smart from ground up, fit loosely into three broad categories: Robots, Drones and Autonomous vehicles • Existing (non-intelligent) things are being upgraded by creating a digital twin, which is a dynamic software model of a physical thing, employing sensors. • The idea of modeling the much larger number of common things — cars, buildings and consumer products — from virtual models, with functional behavior embedded to make day-to-day decisions about the physical world, is emerging REFERENCE LINKS how-machine-learning-and-ai-will-drive-digital-transformation/ chatbots-the-protege-of-ai-data-sciences/
  4. 4. 3. VIRTUAL REALITY AND AUGMENTED REALITY Immersive technologies, such as VR and AR, are part of a new wave of computing devices that transform the way individuals interact with one another and with software systems. • Head Mounted Displays (HMDs) and the device-mesh-based apps & services that power them represent new forms of user interaction that will enable new types of consumer and workplace behaviors • Using Virtual Reality (VR), employees can conduct VisualInspection for site inspections, and Training Process for many equipment use scenarios, including ones, such as catastrophic malfunction, that don't happen often, but that need immediate attention. • Augmented Reality (AR) has a high scope of implementation in Factory Settings and Warehouse Productivity Optimization, like significant increase in picking process REFERENCE LINKS industry-redefined-through-data-sciences/
  5. 5. 4. BLOCKCHAINS AND DISTRIBUTED LEDGERS Blockchain and distributed-ledger concepts are gaining attention, because they hold the promise to transform industry operating models. Multiple business use cases are yet to be proven, but 52% of those surveyed believe that blockchains will affect their business (Gartner). • Using a public blockchain will potentially remove the need for central authorities in arbitrating transactions. This is because there is inbuilt trust in the model through immutable records on a distributed ledger. • Recent versions of distributed ledgers will incorporate assets, data and executable programs allowing for customized applications. • A critical aspect of blockchain technology today is the unregulated, ungoverned creation and transfer of funds, which also concerns regulators and governments. . The debates about permissioned, permissionless, hybrid and private ecosystems and governance will force a more-robust analysis of distributed ledgers. As these analyses are completed, workable solutions will evolve. REFERENCE LINKS sciences-fintech-companies-for-competitive-disruption-advantage/
  6. 6. 5. CONVERSATIONAL SYSTEMS A conversational system uses a conversational UI as its main interface mode. People and machines will communicate across a wide range of mesh devices (such as sensors, appliances and IoT systems). Immersive, continuous and contextual user experience elements will enable this communication using a range of input/output modalities (such as sight, sound, touch, smell, taste and radar). • NLP will rapidly replace rule-based synonym and phrase substitution approaches. • Dynamic natural-language ontologies or knowledge graphs at multiple levels of specificity will be needed to support NLP capabilities, such as disambiguation, concept identification and relationship extraction. • VPA experiences will improve as the AI back end for VPA systems continues to evolve and providers open up their systems for developers to provide tighter links to their applications for targeted scenarios. REFERENCE LINKS chatbots-the-protege-of-ai-data-sciences/ how-machine-learning-and-ai-will-drive-digital-transformation/
  7. 7. 6. MESH APP AND SERVICE ARCHITECTURE The mesh app and service architecture (MASA) is a multichannel solution architecture that supports multiple users in multiple roles using multiple devices and communicating over multiple networks to access application functions. Monolithic applications will be refactored into reusable microservices and shared modular miniservices that reduce the scope of a service down to an individual capability. • Serverless computing is an abstraction model building which is gaining ground, in which, the provider fully manages the infrastructure (for example, virtual machines) to serve application requests so that the developer doesn't have to think about the server resources. • MASA approaches will shift to an "events first, response second" approach during the next five years. Traditional request-driven approach is also essential to modern business, but in the intelligent digital mesh, the main focus will shift toward the event-driven model REFERENCE LINKS sophistication-in-analytics-enter-data-science/ grail-of-data-sciences-liquid-insights-amplified-intelligence-succinct- recommendations/
  8. 8. 7. DIGITAL PLATFORM VIEW OF BUSINESS A platform provides the business with a foundation where resources can come together — sometimes quickly and temporarily, sometimes in a relatively fixed way — to create value. As digitalization moves from an innovative trend to a core competency, enterprises will understand and exploit platform effects throughout all aspects of their businesses. • The platform viewpoint will give you a technology anchor model to guide technology vision, reducing complexity and redundancy • The deepening of digital means that lines are becoming increasingly blurred, and boundaries semi porous — both inside and outside the enterprise — as multiple networks of stakeholders bring value to each other by exploiting and exploring platform dynamics • CIOs are clearly being given the opportunity to lead a digital transformation that exploits platform effects majorly in managing delivery, talent and executing leadership. REFERENCE LINKS themes-to-master-in-digital-business/
  9. 9. THANK YOU SAMEER DHANRAJANI Global Business Leader, Cognizant Analytics & Data Sciences