cognitive computing

What do these market-defining trends have in common? · Analytics for all · Analytics as competitive differentiator · Internet of Things · Artificial intelligence/Machine learning/Cognitive computing · Real-time analytics/event management They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise? It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital i

Today, everything computes. Intelligence has been infused into things no one would recognize as computers: appliances, cars, roadways, clothes, even rivers and cornfields. Tomorrow, many of these things will think, thanks to breakthroughs in cognitive computing. Even the things that don’t think themselves will continue collecting and reporting the massive quantities of data that feed cognitive systems.

In this six-step guide, we aim to help you solve your data challenges to prepare for advanced analytics, cognitive computing, machine learning and the resulting benefits of AI. We’ll show you how to get your data house in order, scale beyond the proof of concept stage, and develop an agile approach to data management. By continually repeating the steps in this guide, you’ll sharpen your data and shape it into a truly transformational business asset. You’ll be able to overcome some of the most common business problems, and work toward making positive changes: • Improve customer satisfaction • Reduce equipment outages • Increase marketing campaign ROI • Minimize fraud loss • Improve employee retention • Increase accuracy for financial forecasts

Je besser die Daten, desto besser die Künstliche Intelligenz Sie möchten Ihre Kunden und deren Verhalten besser verstehen? Ihnen eine maßgeschneiderte Customer Experience bieten? Oder neue Geschäftsfelder identifizieren? Es ist vielleicht nicht immer offensichtlich: Aber die Grundlage jeder gut funktionierenden KI sind Daten. In unserem Leitfaden zeigen wir Ihnen in sechs Schritten, wie Sie Ihre Daten auf innovative Weise organisieren. So schaffen Sie eine optimale Grundlage, um künftig das Beste aus künstlicher Intelligenz, Cognitive Computing und maschinellem Lernen herausholen zu können.

With the proliferation of health and fitness data due to personal fitness trackers, medical devices and other sensors that collect real-time information, cognitive computing is becoming more and more important. Cognitive computing systems, with the ability to understand, reason and learn while interacting with human-generated data, enable providers to find meaningful patterns in vast seas of information. IBM Watson Health is leveraging the power of cognitive computing to help providers make data-driven decisions to improve and save lives worldwide, while controlling healthcare costs. Read our whitepaper and learn about the new era of cognitive computing and how it can improve health outcomes, optimize care and engage individuals in making healthy choices.

As the world of traditional manufacturing fuses with information technology, organizations are tapping into a level of technical orchestration never attainable before. Symphonies of systems facilitate real - time interactions of people, machines, assets, systems, and things. This is the Smart Factory; the factory ecosystem of the future. It is an application of the Industrial Internet of Things (IIoT) built with sets of hardware and software that collectively enable processes to govern themselves through machine learning and cognitive computing

As organizations develop next-generation applications for the digital era, many are using cognitive computing ushered in by IBM Watson® technology. Cognitive applications can learn and react to customer preferences, and then use that information to support capabilities such as confidence-weighted outcomes with data transparency, systematic learning and natural language processing. To make the most of these next-generation applications, you need a next-generation database. It must handle a massive volume of data while delivering high performance to support real-time analytics. At the same time, it must provide data availability for demanding applications, scalability for growth and flexibility for responding to changes.

New channels and cashless payment ecosystems have created greater risk for financial institutions; the increase in fraudulent activities has compounded the need for more rapid detection and counter measures. Please view this webcast and learn: - The key challenges financial institutions face in rapidly detecting, responding and countering new fraud schemes - The value a cognitive computing approach offers an institution; enabling them to make swifter, more accurate decisions while providing more control and transparency

What if an analytics system learned and continue to learn as it experienced new information, new scenarios, and new responses? This is referred to as cognitive computing and is key to providing an analytics system that is easy to use but extremely powerful. Listen to this webinar, led by Jackie Ryan, the Director of Product Management for IBM's Smarter Workforce Portfolio, and learn about: The evolution of cognitive computing How cognitive computing transforms HR How to get started with cognitive talent analytics

What do these market-defining trends have in common? · Analytics for all · Analytics as competitive differentiator · Internet of Things · Artificial intelligence/Machine learning/Cognitive computing · Real-time analytics/event management They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise? It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital is also a

By taking full advantage of the integration and advanced capabilities currently being offered by leading counter fraud solution providers - including predictive analytics and cognitive computing - enterprises can expect to achieve significantly better outcomes.Aberdeen Group's analysis helps to quantify the value of counter fraud analytics in the insurance industry.

Analytics has permeated, virtually, every department within an organization. It’s no longer a ‘nice to have’. It’s an organizational imperative. HR, specifically, collects a wealth of data; from recruiting applications, employee surveys, performance management data and it sits in systems that remain largely untapped. This data can help drive strategic decisions about your workforce. Analytic tools have, historically, been difficult to use and required heavy IT lifting in order to get the most out of them. What if an analytics system learned and continue to learn as it experienced new information, new scenarios, and new responses. This is referred to as Cognitive Computing and is key to providing an analytics system that is easy to use but extremely powerful.

Reliable Transportation For Dummies shows you what it takes to keep a fleet operating efficiently. Learn how to achieve higher service levels at lower cost using proven asset management processes, Internet of Things data and new cognitive computing capabilities.

"When the CMO Council recently asked more than 200 senior marketing decision makers how effectively they have aligned physical and digital experiences, half admitted that these integrated experiences were selective, at best. Yet it is alignment, consistency and connection that drive the foundational relationship between the brand and the buyer. The CMO Council, in partnership with IBM, will host a one-hour interactive webcast with industry-leading media, entertainment and telecommunications marketers to discuss how audience insights across the digital and physical experience have been turned into action, allowing these brands to personalize and enrich each engagement. Multiple case studies will also be discussed during the webcast that focus on the power of segmentation and innovations around cognitive computing. Speakers include Liz Miller, Senior Vice President of Marketing for the CMO Council; Jody Sarno, Dedicated Client Partner, Communications Industry for IBM; Chris Crayner, Ch

Prepare competency frameworks to leverage AI and cognitive computing to transform your HR strategy.

How do manufacturers get beyond the obstacles and barriers to increase cognitive manufacturing maturity? The obstacles encountered by our respondents are tied to organizational maturity. Overcoming them is fundamental to increase cognitive manufacturing success. In this report, we’ll first describe cognitive computing and how it gives rise to cognitive manufacturing. Then, we’ll review specific study findings and recommend actions for electronics executives.

Strong patient engagement leads to improved population health, a better experience of care, and lower healthcare costs. Even so, few healthcare organizations have a well-defined patient engagement strategy, according to research by IBM Watson Health. Read this whitepaper and learn why healthcare organizations should create a comprehensive patient engagement strategy, what each component of such a strategy entails and how to take the steps required to build an effective patient engagement program. From patient portals, telemedicine, and mobile health, to data sharing, automation tools and cognitive computing, you’ll gain the ability to leverage valuable tools for increasing patients’ involvement in their own health outcomes.

From the impact of disruptive technologies to the imperative of digital transformation, businesses today must find new ways to innovate or risk being left behind. While data flowing rapidly between the Internet of Things and multi-cloud computing environments brings tremendous opportunity, there’s also a great deal of complexity. Artificial intelligence (AI) and machine learning (ML) are part of the new wave of solutions capturing the minds of enterprise leaders to respond to these new opportunities and complexities. Digitally literate leaders who are highly cognizant of this wave, are jumping in headfirst and applying AI and ML to solve real business challenges—making enterprise goals of enabling cost savings via smarter operations and decision making come to fruition. BMC Cognitive Service Management (CSM) addresses the complexities of multi-cloud computing by applying intelligence, automation, and predictive capabilities. CSM employs a differentiated approach with a more holistic

Learn how BMC Cognitive Service Management (CSM) addresses the complexities of multi-cloud computing by applying intelligence, automation, and predictive capabilities

Analytics has permeated, virtually, every department within an organization.

Analytics has permeated, virtually, every department within an organization. It’s no longer a ‘nice to have’. It’s an organizational imperative. HR, specifically, collects a wealth of data; from recruiting applications, employee surveys, performance management data and it sits in systems that remain largely untapped. This data can help drive strategic decisions about your workforce. Analytic tools have, historically, been difficult to use and required heavy IT lifting in order to get the most out of them. What if an analytics system learned and continue to learn as it experienced new information, new scenarios, and new responses. This is referred to as Cognitive Computing and is key to providing an analytics system that is easy to use but extremely powerful.

Analytics has permeated, virtually, every department within an organization. It’s no longer a ‘nice to have’. It’s an organizational imperative. HR, specifically, collects a wealth of data; from recruiting applications, employee surveys, performance management data and it sits in systems that remain largely untapped. This data can help drive strategic decisions about your workforce. Analytic tools have, historically, been difficult to use and required heavy IT lifting in order to get the most out of them. What if an analytics system learned and continue to learn as it experienced new information, new scenarios, and new responses. This is referred to as Cognitive Computing and is key to providing an analytics system that is easy to use but extremely powerful.

Analytics has permeated, virtually, every department within an organization. It’s no longer a ‘nice to have’. It’s an organizational imperative. HR, specifically, collects a wealth of data; from recruiting applications, employee surveys, performance management data and it sits in systems that remain largely untapped. This data can help drive strategic decisions about your workforce. Analytic tools have, historically, been difficult to use and required heavy IT lifting in order to get the most out of them. What if an analytics system learned and continue to learn as it experienced new information, new scenarios, and new responses. This is referred to as Cognitive Computing and is key to providing an analytics system that is easy to use but extremely powerful.

What defines cognitive manufacturing maturity? Our study found three stages of cognitive manufacturing maturity. We call those organizations in the earliest stage Observers, followed by Starters and Actives, respectively. These groups differ on two key characteristics: the presence of an overall strategy for cognitive manufacturing, and degree of strategic execution of multiple projects that enable higher project success and significantly fewer failed projects. Strategy is the crucial enabler of higher maturity. How do manufacturers get beyond the obstacles and barriers to increase cognitive manufacturing maturity? The obstacles encountered by our respondents are tied to organizational maturity. Overcoming them is fundamental to increase cognitive manufacturing success. In this report, we’ll first describe cognitive computing and how it gives rise to cognitive manufacturing. Then, we’ll review specific study findings and recommend actions for electronics executives.

IBM has a unique position in the marketplace, with cognitive platforms and services, industry-specific offerings and expert consulting to support electronics companies. To understand how the electronics industry is applying cognitive computing to manufacturing, the IBM Institute for Business Value surveyed 140 electronics executives around the world and across all industry subsectors. We found that a core group of early adopters has kicked off a new generation of production success with cognitive manufacturing and show greater returns on investment (ROI) with increased productivity. Our analysis answers some important questions.